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Does Daylight Saving Save Electricity? A Meta-Analysis
Abstract
The original rationale for adopting daylight saving time (DST) was energy savings. Modern research studies, however, question the magnitude and even direction of the effect of DST on electricity consumption. Representing the first meta-analysis in this literature, we collect 162 estimates from 44 studies and find that the mean reported estimate indicates slight electricity savings: 0.34% during the days when DST applies. The literature is not affected by publication bias, but the results vary systematically depending on the exact data and methodology applied. Using Bayesian model averaging we identify the most important factors driving the heterogeneity of the reported effects: data frequency, estimation technique (simulation vs. regression), and, importantly, the latitude of the country considered. Electricity savings are larger for countries farther away from the equator, while subtropical regions consume more electricity because of DST.
... The typical implementation of DST/DDST involves shifting clocks forward by one hour or more in the spring while setting back in autumn to shift to standard time, and DDST refers to a two-hour temporal adjustment (Havranek et al., 2018). The development timeline of the DST (Figure 1) shows that the DST has been widely carried out for more than five decades (Bellia et al., 2020). ...
... To curb energy consumption, many countries have started to implement DST/DDST (Hunt, 1980). As of 2017, 77 countries and regions were implementing DST/DDST, encompassing more than a quarter of the global population, estimated at more than 1.5 billion individuals (Havranek et al., 2018). ...
... The efficacy of DST is strongly correlated with geographical latitude, with greater electricity savings associated with countries experiencing longer daylight hours during summer; as latitude approaches the equator, the extent of these savings diminishes (Bellia et al., 2020). Havranek et al. established a positive linear relationship between latitude and electricity savings, emphasizing that DST/DDST yields the highest electricity conservation in regions with protracted daylight hours (Havranek et al., 2018). The latitudinal span of the Chinese territory, spanning nearly 50 degrees from north to south, has hindered the consensus on comprehensive DST/DDST implementation in China. ...
(Double) Daylight Saving Time (DST/DDST) synchronizes human daily activities with sunlight hours, aiming to save energy. China implemented DST/DDST in 1986 and annulled it in 1991, which has not since been observed. This study aims to revisit the household lighting energy-saving potentials of DST/DDST implementation in six representative highly urbanized Chinese cities across different latitudes and within different climate zones, based on the electricity consumption behaviour of Chinese people in the 2020s. We constructed country-specific Multiple Linear Regression (MLR) analysis models interrelated with the local characteristic features of the DST/DDST in China, including latitude, age structure, industrial structure, get-up and bedtime schedules. The results showed the following: (1) Both DST and DDST can effectively reduce household lighting consumption in all the studied case cities, while DDST has a superior energy-saving potential; (2) Considering China-specific lifetime schedules, April to October is the most recommended duration for DST/DDST implementation; (3) Northern cities in China exhibit greater potential for energy savings in lighting than southern regions. (4) Cities with larger portions of primary industry have more household lighting-saving potential in China. Based on the obtained results, monthly data and separate statistical data on household lighting could help promote the precision of regression models.
... Mirza (2017) and analyze the overall and hourly effects, accounting for different sets of control groups, various weather conditions, temperature specifications, macroeconomic indicators, cyclicities, and seasonalities. The second part of our analysis uses the results of a meta-analysis by Havranek et al. (2018a), who construct a synthetic best-practice study to estimate the overall DST effect. We extrapolate their Bayesian model averaging benchmark results and the preferred design of the best-practice study on the Slovak electricity market. ...
... The decision on the resulting permanent time will, however, be made individually by each EU member, and some studies (such as Havranek et al., 2018a) indicate that the impact of DST is likely to be country-specific: some EU countries benefit from DST, whereas others consume more electricity because of the policy. Bergland and Mirza (2017) provide insight into the effects of DST in EU member states and show that the effects do indeed differ by state. ...
... Only one known estimate of the electricity savings from DST in Slovakia exists: the cross-country study of Bergland and Mirza (2017), who evaluate the savings because of DST at 1% of power consumption (and provide estimates for many countries, without focusing on Slovakia). The estimates of the effect of DST for the structurally most similar economy to Slovakia would be those of the Czech Republic, the average of which is close to 0% in terms of overall electricity consumption (Kozuskova, 2011;Castoralova, 2019;Havranek et al., 2018a;Bergland and Mirza, 2017;Jilek, 2000). Bergland and Mirza (2017) and Havranek et al. (2018a) find large country heterogeneity in the literature on DST effects on energy savings. ...
The European Union has recently decided to stop the policy of biannual clock changes in 2021. One reason is that the original rationale for the policy, energy savings, is not supported by a large portion of recent empirical studies. Whether the new permanent time will be standard time or the former daylight saving time has not been decided. Evidence on energy savings from daylight saving time is country-specific, and each country may choose its own time. We examine the effects of the policy in a country for which no studies on daylight saving exist, Slovakia. Using hourly data from the 2010–2017 period, we apply a difference-in-differences approach and estimate energy savings to equal 1% of annual electricity consumption. Alternatively, extrapolating the effect from the results of a previous meta-analysis on different countries, for Slovakia we obtain a smaller estimate, unlikely to exceed 0.5%. Moreover, our findings suggest that daylight saving time smooths the electricity demand curve.
... Early implementations of DST in Canada, the United Kingdom and Germany took place in the first decades of the 20th century, aiming at saving electricity. The energy crisis of the 1970s prompted adoption of the practice in most European countries and North America, and in some other jurisdictions, affecting population of more than 1.5 billion in 2017 [1]. Many studies examined the actual energy saving which results from practicing DST. ...
... In most cases the benefits were found to be quite small. Havranek et al. [1] surveyed 162 estimates from 44 studies and found that the mean reported impact indicated only slight electricity savings (0.34%) during the days when DST was applied, with the electricity savings increasing in countries that are located farther away from the equator. The abrupt change in the timing of daily activities on the days of DST clock change has been shown to result in different health effects, e.g., increased rate of acute myocardial infarction [2], increased daily mortality [3], and excess risk of fatal road accidents [4]. ...
Implementation of Daylight Savings Time (DST) started in various jurisdictions during the first half of the 20th century. Much debate on the merits of the twice-yearly change in the official local time has ensued since then regarding energy usage, sleep patterns, health outcomes, traffic safety, etc. The DST switch in the official time abruptly shifts anthropogenic emissions that are related to human activities relative to the Coordinated Universal Time (UTC) but does not affect meteorological processes that disperse them, which day-to-day variability is affected by longer time scales. Here, we utilized the DST clock changes as a repeating biannual experiment to study the impact of meteorology on air pollution. We analyzed traffic volume data and up to 20 years of nitrogen oxides (NOx), fine particulate matter (PM2.5), ozone (O3) and carbon monoxide (CO) concentrations, observed at different air quality monitoring (AQM) stations in Israel, demonstrating a clear and significant impact of the daily meteorological cycle on traffic related air pollution (TRAP). In particular, traffic emissions are prerequisite for TRAP, but meteorology was found to dominate the daily patterns of the NOx, O3 and CO concentration fields in the study area. On the other hand, the impact of vehicle emissions on PM2.5 concentrations seems to be very small. Our results highlight the multiscale interplay between pollutant emissions and dispersion processes, especially for pollutants that are emitted near the surface. We demonstrate that while DST clock changes do not affect the emissions intensity, nor the meteorological processes vigor, they do shift human activity-related emissions with respect to the DST-blind dispersion processes. This results in short-term effects on primary traffic-related pollutant concentrations that cancel out over the day, and a consistent yet small effect on secondary traffic-related pollutant concentrations (O3).
... In the literature, there are controversial papers that propose just the opposite. For instance, whilst studies Havranek et al. (2018) suggest that the DST policy has no effect on energy consumption, Mirza and Bergland (2011) claims the country would save 1% of electricity consumption (Krarti and Hajiah, 2011) argues that the DST policy causes an increase in energy consumption. These three different results showed us, DST policy is complicated and hard to clarify the proper solution. ...
... The studies underline that impact of DST on energy consumption depends on the climate, geographical properties and mathematical location (longitudes and altitudes) of the country or the region (Bellia et al., 2020;Bergland et al., 2017;Aries and Newsham, 2008). Moreover, the article Havranek et al. (2018) suggests that with increasing altitude, or as you go from the equator to the north and south poles, the energy savings will increase. ...
Daylight Saving Time is argued to be effective in saving energy. Turkey is one of the few countries that annulled the clock changes and remained in the summertime zone in 2016. Therefore, the country provides a unique natural experiment to test and confirm this policy change. This paper studies the impact of clock changes on electric energy consumption and load shift. We use historical electrical energy consumption, electricity prices, and relevant atmospheric essential climate variables data in Turkey between 2012-2020. We adopt Multiple Linear Regression, Difference in Differences and Interrupted Time Series methodologies to analyse the historical data. This paper shows that the Daylight Saving Time policy does not lead to a measurable amount of electrical energy savings. Furthermore, it does not cause a noticeable continuous daily load shift throughout the year. We also claim that our findings should apply to countries such as the United States, India, Japan, Australia or China, and continents of Africa and South America, whose latitudes are between 42.0 • north and south of the equator.
... In the literature, there are controversial papers which propose just the opposite. For instance, whilst studies [21] suggest that the DST policy has no effect on energy consumption, [19] claims the country would save 1% of electricity consumption, [14] argues that the DST policy causes an increase in energy consumption. ...
... The studies underline that impact of DST on energy consumption depends on the climate, geographical properties and mathematical location (longitudes and altitudes) of the country or the region [17], [48], [49] .Moreover, the article [21] suggests that with increasing altitude, or as you go from equator to the north and south poles, the energy savings will increase. ...
Daylight Saving Time is argued to be effective in saving energy. Turkey is one of the few countries that annulled the clock changes and remained in the summertime zone in 2016. This paper uses Multiple Linear Regression and Interrupted Time Series methods to study the impact of clock changes on energy consumption and load shift. We use historical energy consumption, electricity prices, and relevant atmospheric essential climate variables data in Turkey between 2012-2020. This paper shows that the Daylight Saving Time policy does not lead to a measurable amount of energy savings. Furthermore, it does not cause a noticeable continuous daily load shift throughout the year. We also claim that our findings should be applicable to those countries such as the United States, India, Japan, Australia or China and as well as continents of Africa and South America, whose latitudes are in between 42.0° north and south of the equator.
... This last topic has been underlined also in more recent works, for example, in Havranek et al. (2018). The researchers have collected 162 estimates from 44 studies, related to different locations and characterized by different outcomes and have established mean electricity savings equal to about 0.34% when DST are applied. ...
... It was demonstrated that, abolishing DST, avoiding the one-hour shift during the spring-summer period and maintaining the local time all the year (winter time) would determine a reduction of DA (with a consequent increment of energy consumption) generally lower than 6%. This DA decrease is more consistent for cities characterized by higher latitude in accordance with what reported by Havranek et al. (2018), This demonstrate the effectiveness of DST in reducing energy consumptions. Considering the effect on circadian system, the application of winter time would determine an increase of CSA values, that can be consistent for northern cities where it can reach 16% (Copenhagen and Stockholmcentral point of the gridsouth orientation). ...
Nowadays, there is an in-depth debate about the suitability of daylight saving time. The shift of one hour during summer time allows a better use of daylighting reducing energy consumptions. However, the impact of daylight saving time on the human health has not been quantified in most of the scenarios. The aim of this study is to determine the impact of daylight saving time on the health of occupants (by calculating Circadian Stimulus Autonomy) and on the energy consumptions for lighting (by calculating Daylight Autonomy) in office buildings. A standard office is analyzed in eleven representative locations of Europe and for three different time schedules: with daylight saving time, with continuous winter time and with continuous summer time. Despite restricted to a specific case study, results provide elements useful to evaluate pros and cons in maintaining daylight saving time, confirming that they are strongly dependent on the geographical position and on the local luminous climate. It was demonstrated that, abolishing daylight saving time, maintaining the local time all the year (winter time), would determine a reduction of Daylight Autonomy generally lower than 6% and that this decrease would be more consistent for cities characterized by higher latitude. At the same time an increase of Circadian Stimulus Autonomy values would be obtained, more consistent for northern cities (maximum observed increment 16%). On the other hand, applying the one-hour shift for the entire year (summer time) would not determine benefits in terms of energy savings nor of impact on circadian system.
... Some metaanalyses capture the number of observations, others capture the Tstatistic ( Doucouliagos and Paldam, 2006) or standard error (Havranek et al., 2015), some even include the date of collection, which gives a panel of studies (Havranek et al., 2018). ...
... The use of expert data merits a specific discussion. The classical metaanalysis framework relies on two main equations ( Doucouliagos and Paldam, 2006) : As shown by the dataset used in (Havranek et al., 2018), the absence of statistical tests in some studies, though infrequent, is not an obstacle to conducting a rigorous metaregression, although it might be expected that introducing too high a proportion of studies without significance testing could weaken the ability to arrive at conclusions. ( Carré et al., 2015) also conducted a meta regression using data without variance of the estimates, which confirmed that the methodology is feasible with expert data. ...
By 2018, about one billion people were living without electricity. The extension of electrical grids is facing many challenges that jeopardize the sustainability of traditional electrification. Decentralized Electrification Projects (DEP) now offer feasible solutions for offgrid access to electricity in developing countries. This thesis explores the role of the demand for reliability of the electricity service as a determinant of sustainable extension of the electrical grid, and the efficiency of electricity supply by DEP to achieve the sustainable development goals. With data on outages observed by households in Kenya, the first chapter establishes the households' preference for the reliability of electricity service, which could be the major lever for effective network expansion. In the second chapter, a meta-analysis consolidating 112 decentralized project evaluations shows that technology, capacity and governance support the design choices that are most critical to achieving the sustainable development goals. The third chapter explores the range of objectives achieved by decentralized electrification practices. The most effective are those that address productive uses and public services, as well as micro-networks in remote areas, which have positive impacts on information and communication. The likelihood of positive impacts increases with the capacity of solar home systems, which favor health and education.
... According to Havraneck, Herman Irsova [19], the standard econometric model that is used to evaluate DST relates the natural logarithm of electricity consumption with DST and a set of control variables. In particular, several articles such as Halvorsen [20], Silk and Joutz [21], Medlock and Soligo [22], and Holtedahl and Joutz [23] estimate electricity demand functions that depend on economic factors such as price and income, as well as weather conditions. ...
... This represents 0.61% of total consumption. It is important to mention that these figures are in line with previous estimates in Mexico that were obtained using other methods; but are large in comparison to the 0.34% mean of the literature reported in the meta-analysis [19]. We also find that DST does not reduce consumption homogeneously during the whole period in which this energy saving practice takes place (from April to October). ...
Since the First World War, several countries use daylight saving time (DST). However, evaluations of DST started until the 1970s. Given the difficulties of finding data around the moment in which DST started, econometric studies usually evaluate changes to DST.
We have aggregate data on residential electricity consumption in Mexico from 1982 to 2016. DST started in 1996. Therefore, our data covers a large period both before and after DST started. Moreover, DST is in effect only during part of the year (from April to October). Hence, we can evaluate the effects of DST with a differences-in-differences (DID) econometric approach.
As far as we know, there is only another DID econometric study using similar data. Such study takes advantage of a short period in which DST was adopted and then repealed in Australia. Since our data covers a larger period, we can control for trends in consumption, calculate savings in different DST months, and run robustness tests.
Our estimates indicate that savings due to DST account for 0.5% of total electricity consumption. Nevertheless, the effect of DST is not homogeneous along the period. This is important because estimates based on DST extensions may not reflect the effects of DST itself.
... These biannual changes have not been without adverse consequences [1]. With the ubiquity of energy-efficient lighting and changes in human behavior since DST was first proposed, the energy savings originally promised are often not realized [2]. As such, many governments are now considering eliminating the biannual clock change tradition, which leaves them with the decision around which time to permanently follow. ...
Purpose of review:
Biannual clock changes to and from daylight saving time have been pervasive in many societies for over 50 years. Governments are considering abandoning this practice and choosing a single permanent time.
Recent findings:
Our endogenous circadian clock follows our photoperiod, which changes over the year. The acute disruption caused by changing our clocks can affect safety (motor vehicle and on the job accidents), health (cardiovascular disease, drug overdoses, suicide), and human behavior (sport performance, generosity, and procrastination). Although abandoning the clock change could help avoid these acute harms, choosing the wrong permanent time could lead to chronic circadian misalignment, which could have even more profound implications for health, safety, and human behavior.
Summary:
Ceasing the biannual clock change may be a good choice, but governments need to be mindful of which permanent time to adopt. Many regions of the world already follow the wrong time during standard time, and circadian misalignment would be amplified by moving to permanent daylight saving time. In many regions, Standard Time better aligns with our circadian clock, thus providing a more natural light cycle that minimizes circadian misalignment.
... Worldwide, over 1.5 billion humans are affected by bi-annual clock changes. 1 Clocks are moved 1 hour forward to Daylight Saving Time (DST) in spring and 1 hour back to standard time in autumn. 2 A range of studies demonstrated that especially the transition to DST negatively impacts sleep 2,3 and, in turn, also human behavior. 4 Because sleep is vastly important for work, 5,6 professional life should also be affected by clock changes. ...
Objective: Worldwide, over 70 countries advance their clocks in spring to Daylight Saving Time. Previous research has already demonstrated that the clock change negatively impacts employees at work. However, this research implicitly assumed that the clock change affects everyone to the same extent. In the current study, we propose that the massively prevalent Daylight Saving Time transition may have an effect on employees’ sleep and their work engagement that is dependent upon employees’ chronotype.
Methods: We conducted a longitudinal study with 155 full-time employees who filled out online surveys on three Mondays around the transition to Daylight Saving Time.
Results:
Results showed that the transition to Daylight Saving Time resulted in decreased work engagement measured 1 day as well as 1 week after the transition to Daylight Saving Time. Lower sleep quality (but not shorter sleep duration) partly explained this effect. The negative effect of the transition to Daylight Saving Time on work engagement 1 day after the transition was more pronounced for employees with later chronotypes (“owls”) than for those with earlier chronotypes (“larks”).
Conclusion:
In summary, our study shows that the transition to Daylight Saving Time has an adverse short-time impact on private life and working life and should, therefore, also be considered in organizations. Because later chronotypes are especially prone to adverse effects of the transition, interventions targeted for this group might be especially helpful.
... Weighted averages of the estimated coefficients (posterior means) are computed using posterior model probabilities (akin to information criteria in frequentist econometrics). Each coefficient is also given a Posterior Inclusion Probability (PIP), which is the sum of posterior model probabilities of the models including the relevant variable and indicates how likely such a variable is to be contained in the true model (Havránek et al., 2018). ...
This work attempts to synthetize existing research about the impact of Covid-19 school closure on student achievement. It extends previous systematic reviews and meta-analyses by (a) using a more balanced sample in terms of country composition, (b) considering new moderators (type of data and research design), and (c) including studies on tertiary education students in addition to primary and secondary education students. Our meta-analysis findings show that the pandemic had, on average, a detrimental effect on learning. The magnitude of this learning deficit (about 0.19 standard deviations of student achievement) appears to be roughly comparable to that suffered by students who have experienced a significant disruption in their schooling due to a major natural disaster (e.g., Hurricane Katrina). Students are also found to have lost more ground in math/science than in other subjects. Additionally, one year or more after the first lockdown, students seem to have been unable to catch up on unfinished learning from the pandemic. This result suggests that more efforts should be made to ensure students recover their missed learning in order to avoid negative long-term consequences for them and society.
... An overview of Daylight Saving Time practice worldwide is shown in Figure 1. Proponents of Daylight Saving Time argue that it is important to promote outdoor leisure activity in the evening during the summer, and that adjustment of clock times may reduce criminal activity and modestly save energy (Doleac and Sanders 2015;Havranek et al. 2018). However, Daylight Saving Time is highly debated, and a number of scientific investigations as reviewed by several authors (Meira et al. 2019;Roenneberg et al. 2019aRoenneberg et al. , 2019b) document that it is associated with both short-and long-term health risks, such as sleep deprivation, excessive sleepiness, mood changes, myocardial infarctions and increased hospital admissions. ...
Daylight Saving Time is highly debated and associated with several health risks. Health experts recommend terminating adjusting the clock time, and to keep permanent standard (winter) time year around. The aims of the study were to investigate preferences for keeping or terminating this biannual adjustment of clock times and for permanent standard or summer time, in the general Norwegian population. Furthermore, we aimed to investigate whether such preferences depended on individual chronotype and home address’ latitude/longitude. The online survey included 47,194 participants. Chronotype was measured with the Composite Scale of Morningness (morning types, intermediate types, evening types). Results showed that 78.2% preferred to terminate adjusting the clock time. Summer time year around was preferred by 61.5% whereas 29.1% preferred standard time year around, and 9.4% did not have any preference. Preferences for terminating adjustment of clock times and summer time year around were found in all chronotypes and regardless of living south (latitude 58–59°N), north (latitude 69–71°N), west (longitude 5–6°E) or east (longitude 19–31°E). However, a relatively larger proportion of evening chronotypes preferred to terminate adjusting the clock time compared to morning chronotypes, and relatively more people living north or east preferred termination than people living south or west, respectively. Permanent standard time was more strongly preferred by extreme morning types in comparison with the other chronotypes. In conclusion, nearly four out of five participants reported to prefer to terminate adjusting the clock time, in line with recommendations. However, in contrast to advice from health experts, permanent summer time was preferred by twice as many as permanent standard time. Both chronotype and home address’ latitude and longitude mattered in regard to such preferences, but only to a small degree.
... It employs Mallow's weights, which have been shown by Hansen (2007) to be optimal for frequentist model averaging, and the orthogonalization of model space suggested by Amini and Parmeter (2012). FMA has recently been applied in meta-analysis, for example, by Bajzik et al. (2020); Havranek et al. ( , 2018aHavranek et al. ( , 2018bHavranek et al. ( , 2018c. Also this robustness check corroborates the results we have discussed previously. ...
A key parameter estimated by lab and field experiments in economics is the individual discount rate—and the results vary widely. We examine the extent to which this variance can be attributed to observable differences in methods, subject pools, and potential publication bias. To address the model uncertainty inherent to such an exercise we employ Bayesian and frequentist model averaging. We obtain evidence consistent with publication bias against unintuitive results. The corrected mean annual discount rate is 0.33. Our findings also suggest that discount rates are independent across domains: people tend to be less patient when health is at stake compared to money. Negative framing is associated with more patience. Finally, the results of lab and field experiments differ systematically, and it also matters whether the experiment relies on students or uses broader samples of the population.
... Despite the fact that about 1.6 billion people experience DST worldwide [30], with a mounting debate on its economic benefits [37], the available evidence on the health effect of the shifts in and out of DST is limited [11]: a few studies reported no effects of DST on the risk of stroke [36], manic episodes [38], suicide attempts [39] and spontaneous deliveries [40]. On the contrary, other publications reported an association between DTS shifts and several conditions including fatigue, headache, loss of attention and alertness, reduced motivation [34], traffic and workplace injures [33,41], missed medical appointments [42] and general mortality [11]. ...
Background:
The available evidence on the effects of daylight saving time (DST) transitions on major cardiovascular diseases is limited and conflicting. We carried out the first meta-analysis aimed at evaluating the risk of acute myocardial infarction (AMI) following DST transitions.
Methods:
We searched cohort or case-control studies evaluating the incidence of AMI, among adults (≥18 y), during the weeks following spring and/or autumn DST shifts, versus control periods. The search was made in MedLine and Scopus, up to 31 December 2018, with no language restriction. A summary odds ratio of AMI was computed after: (1) spring, (2) autumn or (3) both transitions considered together. Meta-analyses were also stratified by gender and age. Data were combined using a generic inverse-variance approach.
Results:
Seven studies (>115,000 subjects) were included in the analyses. A significantly higher risk of AMI (Odds Ratio: 1.03; 95% CI: 1.01⁻1.06) was observed during the two weeks following spring or autumn DST transitions. However, although AMI risk increased significantly after the spring shift (OR: 1.05; 1.02⁻1.07), the incidence of AMI during the week after winter DST transition was comparable with control periods (OR 1.01; 0.98⁻1.04). No substantial differences were observed when the analyses were stratified by age or gender.
Conclusion:
The risk of AMI increases modestly but significantly after DST transitions, supporting the proposal of DST shifts discontinuation. Additional studies that fully adjust for potential confounders are required to confirm the present findings.
... Further details on BMA can be found in, for example, Raftery et al. (1997) or Eicher et al. (2011). BMA has been used in meta-analysis, for example, by Havranek et al. ( , 2018aHavranek et al. ( , 2018c. ...
A key parameter in international economics is the elasticity of substitution between domestic and foreign goods, also called the Armington elasticity. Yet estimates vary widely. We collect 3524 reported estimates of the elasticity, construct 32 variables that reflect the context in which researchers obtain their estimates, and examine what drives the heterogeneity in the results. To account for model uncertainty, we employ Bayesian and frequentist model averaging. To correct for publication bias, we use newly developed non-linear techniques. Our main results are threefold. First, there is publication bias against small and statistically insignificant elasticities. Second, differences in results are best explained by differences in data: aggregation, frequency, size, and dimension. Third, the elasticity implied by the literature after accounting for both publication bias and study quality lies in the range 2.5–5.1 with a median of 3.8.
... First proposed by Glass (1976) in 1976, meta-analysis for systematic literature review was introduced in economics by Stanley and Jarrell (Jarrell and Stanley, 1990;Smith and Kaoru, 1990;Stanley and Jarrell, 2005;Weitzman et al., 1990) in 1989 leading to its wide use in the current decade (Havranek et al., 2018), (Nelson and Kennedy, 2009). Assuming study 'i' from a total of 'n' studies in our analysis each with an estimate, y i of the effect of interest, and standard error of this estimate, σ i , fixed effects meta-analysis assumes a single true effect size,θ with homogeneity of effect size across studies. ...
Energy poverty has evolved as an important issue of research from academic and policy perspectives during the last two decades. The energy poverty estimates exhibit widespread variations across regions, methodologies and datasets, making the task of energy and development policies challenging. The variations in energy poverty estimates necessitate a systematic and rigorous analysis of these empirical studies to obtain a true measure of energy poverty. The present study conducts a meta-analysis of 30 studies and 103 estimates of energy poverty. On average, 71.1 percent of the population in the overall sample studies has been identified as energy poor. High I-square statistic values suggest heterogeneity bias in the sample studies; therefore, analysis at the subgroup level has been conducted. Meta-regression analysis of overall sample and subgroups has identified type of methodology, citations, impact factor of the journal, regional dummies, average key crude oil price and gross domestic product as significant factors that explain heterogeneity in the energy poverty effect sizes. We recommend inclusion of local and regional factors in assessment of energy poverty for developing a uniform methodology to assess energy poverty across developing economies.
... New techniques include the weighted average of adequately powered estimates by Ioannidis et al. (2017) and Stanley and Doucouliagos (2017), unrestricted weighted least squares by Stanley andDoucouliagos (2015, 2017), the selection model by Andrews and Kasy (2019), the p-uniform* model by van Aert and van Assen (2019), the endogenous kink model by Bom and Rachinger (2019), and the stem-based estimator by Furukawa (2020). The use of model averaging techniques, both Bayesian and frequentist, has become common (e.g., Havranek et al., 2015;Havranek and Irsova, 2017;Havranek et al., 2018a;Havranek et al., 2018b). Several important contributions have assessed the incidence and impact of publication bias and p-hacking in economics (Brodeur et al., 2016;Bruns and Ioannidis, 2016;Ioannidis et al., 2017;Brodeur et al., 2018;Christensen and Miguel, 2018), and attention has turned to journal editorial policies (Blanco-Perez and Brodeur, 2020). ...
Meta‐analysis has become the conventional approach to synthesizing the results of empirical economics research. To further improve the transparency and replicability of the reported results and to raise the quality of meta‐analyses, the Meta‐Analysis of Economics Research Network has updated the reporting guidelines that were published by this Journal in 2013. Future meta‐analyses in economics will be expected to follow these updated guidelines or give valid reasons why a meta‐analysis should deviate from them.
... On a night between Saturday and Sunday in spring, clocks are set forward one hour to take advantage of the prolonged daylight with the main intention of saving energy. As the expectations for reduced net energy demand were finally not met [1,2], the European Commission decided in 2018 to discontinue DST regulation [3], opening the discussion on possible alternatives in member states. Recently, we had an inspiring coffee-table discussion with colleagues after they had published a scientific letter on that topic [4]. ...
In Europe and many countries worldwide, a half-yearly changing time scheme has been adopted with the aim of optimizing the use of natural daylight during working hours and saving energy. Because the expected net economic benefit was not achieved, the discussion about the optimal solution has been reopened with a shifted focus on social and health related consequences. We set out to produce evidence for this discussion and analysed the impact of daylight saving time on total mortality of a general population in a time series study on daily total mortality for the years 1970–2018 in the city of Vienna, Austria. Daily deaths were modelled by Poisson regression controlling for seasonal and long-term trend, same-day and 14-day average temperature, humidity, and day of week. During the week after the spring transition a significant increase in daily total mortality of about 3% per day was observed. This was not the case during the week after the fall transition. The increase in daily mortality as observed in the week after spring DST-transition is most likely causally linked to the change in time scheme.
... Each variable is then assigned a posterior inclusion probability (PIP), which can be thought of as the Bayesian analogy of statistical significance and is computed as the sum of the posterior model probabilities for the models in which the variable is included. Bayesian model averaging has recently been used in metaanalysis, for example, by Havranek, Herman, and Irsova (2018a), Havranek, Irsova, and Vlach (2018b), Irsova (2017), Havranek, Rusnak, andSokolova (2017), Zigraiova and Havranek (2016), , and Valickova, Havranek, and Horvath (2015). ...
We provide a quantitative synthesis of the literature studying the effect of foreign direct investment (FDI) on the productivity of locally owned firms in the Czech Republic. To this end, we collect 332 previously reported estimates and use Bayesian model averaging to address model uncertainty. We find no evidence of publication bias, i.e. no sign of selective reporting of estimates that are statistically significant and show an intuitive sign. Our results suggest that more advanced techniques yield substantially larger positive effects (FDI spillovers). When placing more weight on estimates that solve important identification problems in the literature (such as using data on existing linkages between firms instead of approximations based on input-output tables), we find that, as of 2018, a 10-percentage-point increase in foreign presence is likely to lift the productivity of domestic firms by 11%. The effect is even larger for joint ventures, reaching 19%.
... Despite the fact that about 1.6 billion people experience DST worldwide [30], with a mounting debate on its economic benefits [37], the available evidence on the health effect of the shifts in and out of DST is limited [11]: a few studies reported no effects of DST on the risk of stroke [36], manic episodes [38], suicide attempts [39] and spontaneous deliveries [40]. On the contrary, other publications reported an association between DTS shifts and several conditions including fatigue, headache, loss of attention and alertness, reduced motivation [34], traffic and workplace injures [33,41], missed medical appointments [42] and general mortality [11]. ...
Background
The current evidence on the effects of daylight saving time (DST) transitions on major cardiovascular diseases is limited, and available results are conflicting. We carried out the first meta-analysis aimed at evaluating the risk of acute myocardial infarction (AMI) following DST transitions.
Methods
We searched MedLine and Scopus up to December 31, 2018, with no language restriction, to retrieve cohort or case-control studies evaluating AMI incidence among adults (≥18y) in the week following spring and/or autumn DST shifts versus control periods. A summary relative risk of AMI was computed after: (1) spring, (2) autumn, (3) both transitions considered together versus control weeks. Stratified analyses were performed by gender and age. Data were combined using a generic inverse-variance approach.
Results
Seven studies (>115,000 subjects) were included in the analyses. A significantly higher risk of AMI (Odds Ratio: 1.03; 95% CI: 1.01-1.06) was observed in the two weeks following spring or winter DST transitions. The risk increase was however significant only after the spring shift (OR: 1.05; 1.02-1.07), while AMI incidence in the week after winter DST transition was comparable to control periods (OR 1.01; 0.98-1.04). No substantial differences by age or gender emerged.
Conclusions
The risk of AMI increases modestly but significantly following DST transitions, supporting the proposal of DST shifts discontinuation. Additional studies fully adjusting for potential confounders are required to confirm the present findings.
Key messages
The risk of acute myocardial infarction increases modestly but significantly following DST transitions. Although preliminary, our findings support the proposal of DST shifts discontinuation.
... Instead we opt for Bayesian model averaging (BMA), which was designed specifically to tackle model uncertainty (Raftery et al., 1997). BMA has recently been used in the applications of meta-analysis in economics and finance by Valickova et al. (2015), Zigraiova and Havranek (2016), Havranek and Irsova (2017), , Havranek et al. (2018a), Havranek et al. (2018b), Havranek et al. (2018c), andHavranek et al. (2019). ...
We show that three factors combine to explain the mean magnitude of excess sensitivity reported in studies estimating the consumption response to income changes: the use of macro data, publication bias, and liquidity constraints. When micro data are used, publication bias is corrected for, and households under examination have substantial liquidity, the literature implies little evidence of deviations from consumption smoothing. The result holds when we control for 45 additional variables reflecting the methods employed by researchers and use Bayesian model averaging to account for model uncertainty. The estimates produced by this literature are also systematically affected by the size of the change in income and the chosen measure of consumption.
... A 2017 meta-analysis of 44 studies comprehensively states that DST saves ∼0.34% of energy in respective countries. As could be expected, there are differences depending on the latitudes of the countries and a larger distance to the equator leads to a higher efficacy of DST (10). Regarding energy management, it may therefore be reasonable to keep seasonal clock changes in countries with high variation of daylight hours, but to abandon them in other regions. ...
Today, daylight saving time is observed in nearly 80 countries around the world, including the European Union, the USA, Canada, and Russia. The benefits of daylight saving time in energy management have been questioned since it was first introduced during World War I and the latest research has led to varying results. Meanwhile, adverse effects of seasonal time shifts on human biology have been postulated and the European Union is planning to abandon the biannual clock change completely. Medical studies have revealed a correlation of seasonal time shifts with increased incidences of several diseases including stroke, myocardial infarction, and unipolar depressive episodes. Moreover, studies in mice have provided convincing evidence, that circadian rhythm disruption may be involved in the pathogenesis of inflammatory bowel diseases, mainly by disturbing the intestinal barrier integrity. Here, we present previously unpublished data from a large German cohort indicating a correlation of seasonal clock changes and medical leaves due to ulcerative colitis and Crohn's disease. Furthermore, we discuss the health risks of clock changes and the current attempts on reforming daylight saving time from a medical perspective.
... BMA processes hundreds of thousands of regressions consisting of different subsets of the 18 explanatory variables. With such a large model space (2 18 models to be estimated), we decide to follow some of the previous meta-analyses (such as Havranek and Rusnak, 2013;Irsova and Havranek, 2013;Havranek, Herman and Irsova, 2018a, who also use the bms R package by Feldkircher and Zeugner, 2009) and apply the Markov chain Monte Carlo algorithm, which considers only the most important models. Bayesian averaging computes weighted averages of the estimated coefficients (posterior means) across all the models using posterior model probabilities (analogous to information criteria in frequentist econometrics) as weights. ...
One of the most frequently examined relationships in education economics is the correlation between tuition fee increases and the demand for higher education. We provide a quantitative synthesis of 443 estimates of this effect reported in 43 studies. While large negative estimates dominate the literature, we show that researchers report positive and insignificant estimates less often than they should. After correcting for this publication bias, we find that the literature is consistent with the mean tuition–enrolment elasticity being close to zero. Nevertheless, we identify substantial heterogeneity among the reported effects: for example, male students and students at private universities display larger elasticities. The results are robust to controlling for model uncertainty, using both Bayesian and frequentist methods of model averaging.
... Authors who prefer significant results and disregard insignificant estimates will overreport high t-values (in absolute terms). We follow Stanley (2005), Havranek (2010), and Havranek, Herman, and Irsova (2018) and define the standardized t-statistics T(YED ij ) adjusted for the true effect from Table 2: ...
We present the first study that examines the effects of publication selection in the literature estimating the income elasticity of water demand. Paradoxically, more affected by publication selection are the otherwise preferable estimates that control for endogeneity. Attempting to correct simultaneously for publication and endogeneity biases, we find that the mean underlying elasticity is approximately 0.15 or less. The result is robust to controlling for more than 30 characteristics of the estimates and accounting for model uncertainty. The differences in the reported estimates are systematically driven by differences in the tariffstructure, regional coverage, data granularity, and control for temperature. © 2018 by the Board of Regents of the University of Wisconsin System.
This article provides concise, nontechnical, step‐by‐step guidelines on how to conduct a modern meta‐analysis, especially in social sciences. We treat publication bias, p‐ hacking, and systematic heterogeneity as phenomena meta‐analysts must always confront. To this end, we provide concrete methodological recommendations. Meta‐analysis methods have advanced notably over the last few years. Yet many meta‐analyses still rely on outdated approaches, some ignoring publication bias and systematic heterogeneity. While limitations persist, recently developed techniques allow robust inference even in the face of formidable problems in the underlying empirical literature. The purpose of this paper is to summarize the state of the art in a way accessible to aspiring meta‐analysts in any field. We also discuss how meta‐analysts can use advances in artificial intelligence to work more efficiently.
We examine whether estimates of hedge fund performance reported in prior empirical research are affected by publication bias. Using a sample of 1019 intercept terms from regressions of hedge fund returns on risk factors (the “alphas”) collected from 74 studies published between 2001 and 2021, we show that the selective publication of empirical results does not significantly contaminate inferences about hedge fund returns. Most of our monthly alpha estimates adjusted for the (small) bias fall within a relatively narrow range of 30–40 basis points, indicating positive abnormal returns of hedge funds: Hedge funds generate money for investors. Studies that explicitly control for potential biases in the underlying data (e.g., backfilling and survivorship biases) report lower but still positive alphas. Our results demonstrate that despite the prevalence of publication selection bias in many other research settings, publication may not be selective when there is no strong a priori theoretical prediction about the sign of the estimated coefficients.
We analyse the effect of Daylight Saving Time (DST) on automobile, acute myocardial infarctions (AMI) and crime-related fatalities in Mexico from 1998 to 2018. We rely on a regression discontinuity approach to obtain the causal impact of DST on these three causes of mortality. We find an increase in automobile fatalities of 13% −14% during the fall and spring transitions. Automobile fatalities increase 27% in urban areas during the fall transition and 18% in rural areas for spring. Crime-related fatalities increase 16% for the whole country, 13% in urban areas and 16% in rural areas in the fall transition and 2% in rural areas in the spring transition. The only impact on AMI fatalities that we find is a small increase in urban areas during the spring transition. In general, our results estimate an increase of about 100 more deaths per year due to DST, which translates into a monetary cost of about $22 million U.S. dollars per year.
We investigate the impact of Daylight Saving Time (DST) on electricity demand in the Balearic Islands (Spain), a region characterized by a large tourism industry, and where tourists outnumber residents during the peak season. Using daily data from 2007 to 2017 and deploying a time series model as well as a double/debiased machine learning model, we estimate that DST implementation results in a small positive increase of electricity consumption, although in several cases this effect is not statistically significant. Omitting from the model a variable that measures the number of people present on the islands would lead to an overestimation of the DST effect on electricity consumption.
Unemployment rate forecasting has become a particularly promising
domain of comparative studies in recent years because it is a major issue facing
the economic forecasting process. Since the time-series data are rarely pure linear
or nonlinear, obviously, sometimes contain both components jointly. Therefore, this
study introduces a hybrid model that combines two commonly used models, namely,
the Linear Autoregressive Moving Average with exogenous variable (ARMAX)
model and nonlinear Generalized Autoregressive Conditional Heteroskedasticity
with exogenous variable (GARCHX) model whose conditional variance follows
a General error distribution (GED). That is, build a hybrid (ARMAX-GARCHXGED)
model employed in modeling bivariate time-series data of the unemployment
rate and exchange rate. Usually, the forecasting performance evaluation based on
the common classical forecast accuracy criteria such as Root Mean Squared Error
(RMSE), Mean Absolute Error (MAE), and Mean Absolute Percent Error (MAPE)
have some specific limitations in application to choosing the optimal forecasting
model. Therefore, in this paper, we employed a modern evaluation criterion based
on the methodology advocated by Diebold–Mariano (DM) known as (DM test) as a
new criterion for evaluation based on statistical hypothesis tests. This (DM test) has
been applied in this study to distinguish the significant differences in forecasting accuracy
between hybrid (ARMAX-GARCHX-GED) and individual ARMAX models.
From the case study results and according to DM-test it is observed that the differences
between the forecasting performances of models are significant and the hybrid
model (ARMAX-GARCHX-GED) is more efficient than the individual competitive
ARMAX model for the unemployment rate forecasting.
Several central banks have leaned against the wind in the housing market by increasing the policy rate preemptively to prevent a bubble. Yet the empirical literature provides mixed results on the impact of short-term interest rates on house prices: the estimated semi-elasticities range from to positive values. To assign a pattern to these differences, we collect 1,555 estimates from 37 individual studies that cover 45 countries and 72 years. We then relate the estimates to 39 characteristics of the financial system, business cycle, and estimation approach. Our main results are threefold. First, the mean reported estimate is exaggerated by publication bias, because insignificant results are underreported. Second, inclusion of controls correlated with policy rates (credit or money supply) decreases the estimated effects of policy rates on house prices. Third, the effects are stronger in countries with more developed mortgage markets and generally later in the cycle when the yield curve is flat and house prices enter an upward spiral.
The voluminous empirical research on the effect of financial development on income inequality has yielded mixed results. In this paper, we collect 2127 estimates reported in 116 published studies that investigate the effect of financial development on income inequality. Although our initial tests for publication bias (which do not account for moderator variables) show that the current literature does not suffer from publication selectivity, once we control for a set of moderator variables, we find evidence of mild publication bias in favor of positive estimates (i.e., the current literature favors the publication of studies that find that financial development increases income inequality). In addition, our results suggest that the overall effect of financial development on income inequality is on average zero, but that its sign and magnitude depend systematically on various study characteristics. The characteristics of data and estimation methods, whether endogeneity is taken into account, the different measures of financial development and the inclusion of financial openness, inflation and income variables in the regressions matter significantly for the effect of financial development on inequality.
This is the first meta-study to analyze the effect size of remittances on the real exchange rate (RER). Using 426 estimates from 67 studies, we found that remittances appreciate RER; however, the effect size differs across countries. Compared to global estimates, the mean effect of remittances on RER is significantly larger for East Asia and the Pacific, whereas the same nexus is found to be significantly smaller for Latin America and the Caribbean. Furthermore, the synthesized effect of remittances on RER is found to be significantly positive for lower-middle-income countries. Our empirical examination shows that publication selection bias is less likely in the literature. We found a genuine effect of remittances on RER appreciation. This study also provides policy recommendations and presents suggestions for future research in the field.
The original rationale for the adoption of daylight saving time (DST) was to conserve energy; however, the effects of DST on energy consumption are questionable or negligible. Conversely, there is substantial evidence that DST transitions have the cumulative effect on sleep deprivation with its adverse health effects. In light of current evidence, the European Commission in 2018 decided that biannual clock change in Europe would be abolished. Current indirect evidence supports the adoption of perennial standard time, which aligns best with the human circadian system and has the potential to produce benefits for public health and safety.
We show that the large elasticity of substitution between capital and labor estimated in the literature on average, 0.9, can be explained by three issues: publication bias, use of cross-country variation, and omission of the first-order condition for capital. The mean elasticity conditional on the absence of these issues is 0.3. To obtain this result, we collect 3,186 estimates of the elasticity reported in 121 studies, codify 71 variables that reflect the context in which researchers produce their estimates, and address model uncertainty by Bayesian and frequentist model averaging. We employ nonlinear techniques to correct for publication bias, which is responsible for at least half of the overall reduction in the mean elasticity from 0.9 to 0.3. Our findings also suggest that a failure to normalize the production function leads to a substantial upward bias in the estimated elasticity. The weight of evidence accumulated in the empirical literature emphatically rejects the Cobb-Douglas specification.
Using data provided by the Indiana State Department of Vital Statistics, this study examines the mortality effects of daylight saving time observance using the April 2006 expansion of daylight saving time in Indiana as a natural experiment. The expansion of daylight saving time to all Indiana counties lowered the average mortality rate in the treatment counties during the months in which daylight saving time was observed. Stratified demographic analyses indicate that daylight saving time reduced mortality among males, females, and whites, but only among those aged 65 years and older. Specific-cause analysis indicates that daylight saving time lowered mortality primarily via reduced cancer mortality. The results of this study suggest a novel solar UVB-vitamin D mechanism could be responsible for the reduction in treatment county mortality following the expansion of daylight saving time in Indiana.
A key theoretical prediction in financial economics is that under risk neutrality and rational expectations a currency’s forward rates should form unbiased predictors of future spot rates. Yet scores of empirical studies report negative slope coefficients from regressions of spot rates on forward rates. We collect 3,643 estimates from 91 research articles and using recently developed techniques investigate the effect of publication and misspecification biases on the reported results. Correcting for these biases yields slope coefficients in the intervals (0.23,0.45) and (0.95,1.16) for the currencies of developed and emerging countries respectively, which implies that empirical evidence is in line with the theoretical prediction for emerging economies and less puzzling than commonly thought for developed economies. Our results also suggest that the coefficients are systematically influenced by the choice of data, numeraire currency, and estimation method.
Previous research on the effects of daylight saving time (DST) on electricity consumption has provided mixed results. We use daily state-level panel data on electricity consumption in Australia between 1998 and 2015, during which period there was considerable variation in the presence and timing of DST implementation, as well as in weather conditions and cooling usage within and between states. This provides us with a unique opportunity to study the interaction effects of DST with exogenous variation in daily weather conditions and cooling usage over two decades. Our results show that the effect of DST on electricity consumption depends strongly on weather conditions and cooling usage. Forward DST increases the electricity consumption when temperatures and air conditioner ownership are higher. We provide simulations for countries in the European Union that need to decide on DST adoption in the coming year. Our findings are policy-relevant given rising temperatures and worldwide increases in cooling usage during summer.
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In this work, two analyses are conducted to assess the impact of adopting Daylight Saving Time (DST) on power consumption in the Spanish Electric System. This study was carried out using the short-term electric load forecasting software currently in use in the Spanish Transmission System Operator (TSO). The forecasting software will simulate the case of electrical load in Spain without DST. The results obtained denote that DST may have a positive impact on reducing electric energy demand.
Nous modélisons un marché électrique simplifié avec des producteurs utilisant des générateurs électriques conventionnels ou intermittents et des consommateurs équipés soit de compteurs intelligents avec tarification en temps réel, soit de compteurs traditionnels avec tarification forfaitaire. Nous calculons l’investissement dans les technologies intermittentes et les compteurs intelligents à l’optimum social. Nous montrons que la pénétration optimale des compteurs intelligents croît avec la volatilité du prix de l’électricité au comptant. Il s’ensuit que les capacités de production intermittentes et les compteurs intelligents sont complémentaires, uniquement s’il existe une corrélation négative entre l’énergie intermittente et la demande ou si la capacité des générateurs intermittents est suffisamment importante. Dans le cas contraire, des capacités de production intermittentes plus importantes contribuent en fait à réduire la volatilité du prix de l’électricité au comptant, ce qui rend les compteurs intelligents moins utiles. Nous proposons également une application numérique, calibrée pour représenter le marché électrique français en 2018 et les objectifs politiques pour 2030.
Offshoring, either as FDI or offshore outsourcing, is a phenomenon of increasing importance that has been widely studied in the economics literature. Studies analysing the impact of offshoring on the labour market report divergent results. In this paper we develop a meta-analysis of the empirical literature that estimates the effect of offshoring on wages. We find that, after correcting for the presence of publication bias, the average effect is not significantly different from zero in either the origin or the destination countries. We also find that the wage impact of offshoring depends on methodological characteristics of the primary studies, such as the way offshoring is measured, the nature of goods/services that are offshored, the workers’ skill level, the unit of analysis, the structure of the data, and the estimation technique.
Expatriate workers’ remittances represent an important source of financing for low- and middle-income countries. No consensus, however, has yet emerged regarding the effect of remittances on economic growth. In a quantitative survey of 538 estimates reported in 95 studies, we find that approximately 40% of the studies report a positive effect, 40% report no effect, and 20% report a negative effect. Our results indicate publication bias in favor of positive effects. Correcting for the bias using recently developed techniques, we find that the mean effect of remittances on growth is still positive but economically small. Nevertheless, our results uncover noticeable regional differences: remittances are growth-enhancing in Asia but not in Africa. Studies that do not control for alternative sources of external finance, such as foreign aid and foreign direct investment, mismeasure the effect of remittances. Finally, time-series studies and studies ignoring endogeneity issues report systematically larger effects of remittances on growth.
In empirical research significant diversity of corporate cash holdings speed of adjustment (SOA) estimates can be observed. It is possible that some of the results are affected by publication selection bias. Articles whose results are clearly in line with economic theories may be preferred by authors and reviewers and, consequently, conclusions from this area can be published more frequently. The aim of this article is to verify whether there is a publication selection bias with respect to studies related to corporate cash holdings adjustments and to investigate the sources of heterogeneity in cash holdings SOA estimates. The statistical method used in the study was meta-analysis, which allows a combined analysis of the results from independent research. Meta-analysis enables to verify the occurrence of the publication selection bias and to explain the heterogeneity of the results presented in articles. The study was based on data collected asa result of a review of the literature published between 2003 and 2017. On the basis of information on 402 estimates from 58 different studies it has been shown that the publication selection bias does not occur. The Bayesian Model Averaging was used for modelling. It was identified that the characteristics associated with the data set used in the study, model specification and the estimation method significantly affect the hetero-geneity of corporate cash holdings SOA estimates. This diversity is determined, among others, by the choice of estimation method, length of the period covered by the analysis and characteristics of the market environment of the concerned entities.
en The primary rationale for daylight saving time (DST) has long been energy savings. Whether it achieves this goal, however, remains a subject of debate. Recent studies, examining only one location at a time, have shown DST to increase, decrease or leave overall energy demand unchanged. Rather than concluding the effect is ambiguous, this paper is the first to test for heterogeneous regional effects based on differences in sun times (natural factors) and waking hours (societal factors). Using a rich hourly data set and quasi‐experimental methods applied across Canadian provinces, this paper rationalizes the differing results, finding region‐specific effects consistent with differences in sun times and waking hours. DST increases electricity demand in regions with late sunrises and early waking hours.
Résumé
fr Les économies d'énergie sont la principale justification du passage à l’heure d’été. Néanmoins, la réalisation de cet objectif est sujet à débat: les études récentes basées sur une seule zone géographique ont obtenu des résultats contradictoire sur l’impact de l’heure d’été sur la demande d’énergie. Cet article est la première étude à examiner des hétérogénéités locales basées sur l’heure de levé du soleil (naturel) et l’heure de réveil (sociétal). Exploitant des données horaires et utilisant une approche quasi‐expérimentale sur les provinces du Canada, l’étude réconcilie les résultats divergents par des effets locaux compatibles avec les différences de l’heure de levé du soleil et de réveil. L’heure d’été augmente la demande en électricité dans les régions où le soleil se lève tard et les gens se lèvent tôt.
In this paper, we analyze the effect of light conditions on road accidents and estimate the long run consequences of different time regimes for road safety. Identification is based on variation in light conditions induced by differences in sunrise and sunset times across space and time. We estimate that darkness causes annual costs of more than £500 million in Great Britain. By setting daylight saving time year-round 8 percent of these costs could be saved. Thus, focusing solely on the short run costs related to the transition itself underestimates the total costs of the current time regime.
Firm size is commonly used in numerous empirical asset pricing models as a determinant of expected stock returns. Yet there is little consensus over the magnitude and stability of the size premium. In fact, some researchers even question whether firm size should be used as a pricing factor. We collect 1746 estimates of the slope coefficients capturing the association between firm size and stock returns reported in 102 published studies and conduct the first meta‐analysis on the size premium. We find evidence of a strong bias toward publishing statistically significant negative slope coefficients. After correcting for the bias, we find that the literature implies a difference in annual stock returns on the smallest and the largest New York Stock Exchange (NYSE) market capitalization quintiles of 1.72%. For the time periods covered in the sampled articles, we find that the size premium was larger in earlier years and that the intensity of publication bias has been decreasing over time.
We examine the use of central bank equity as an unconventional monetary policy tool. In this setting, a central bank employs digital currency to transfer digital cash to each household, thus supporting consumption directly when needed. The asset side of the central bank’s balance sheet remains unchanged, and the creation of new digital cash is offset by a decrease in central bank equity. The central bank thus incurs an immediate loss but does not take on any additional risks for its future income statements. We address several objections to this policy, paying particular attention to the claim that weakening the financial strength of the central bank endangers long-term price stability. Through a meta-analysis of 176 estimates reported previously in the literature, we find that central bank financial strength has not historically correlated with inflation performance.
Many studies have estimated the trade effect of the euro, but their results vary greatly. This meta‐analysis collects 3323 estimates of the euro effect along with 28 characteristics of estimation design from almost 60 studies and quantitatively examines the literature. The results show evidence of publication bias, but they also suggest that the bias decreases over time. After correcting for the bias, the meta‐analysis shows that the literature is consistent with an effect ranging between 2% and 6%. The results from Bayesian model averaging, which takes into account model uncertainty, show that the differences among estimates are systematically driven by data sources, data structure, control variables, and estimation techniques. The mean reported estimate of the euro's trade effect conditional on best‐practice approach is 3%, but is not statistically different from zero.
Daylight saving time (DST) affects the lives of more than 1.6 billion people worldwide, with energy saving being the original rationale for its implementation. This study takes advantage of natural experiment data from September 2006 to March 2013 in Western Australia in which DST was observed from December 2006 to March 2009, to estimate the effect of DST on electricity demand. Using the difference-in-differences (DD) approach, we find that DST has little effect on overall electricity demand and electricity generation costs. However, it has a strong redistributional effect by reducing electricity demand substantially in the late afternoon and early evening. This redistributional effect of DST may be of particular interest for policymakers who are interested in controlling high demand and the short term energy market price.
Daylight saving time (DST) affects the lives of more than 1.6 billion people worldwide, with energy saving being the original rationale for its implementation. This study takes advantage of natural experiment data from September 2006 to March 2013 in Western Australia in which DST was observed from December 2006 to March 2009, to estimate the effect of DST on electricity demand. Using the difference-in-differences (DD) approach, we find that DST has little effect on overall electricity demand and electricity generation costs. However, it has a strong redistributional effect by reducing electricity demand substantially in the late afternoon and early evening. This redistributional effect of DST may be of particular interest for policymakers who are interested in controlling high demand and the short term energy market price.
We examine the economic efficiency of incentive mechanisms used to promote Renewable Energy (RE) across the European Union (EU) by looking at returns to investors along with any negative externalities or social costs. Using electricity price data from 2009 to 2013, we evaluate the RE support mechanisms adopted by some of the largest EU economies. We explain the limitations of various metrics used to inform incentives for RE and propose an alternative metric reflecting investor requirements. Our results show that while the EU schemes were effective in delivering RE capacity, the incentives provided were overly generous and economically inefficient. To assess the indirect costs of RE in liberalized electricity markets we employ real option theory to quantify the costs of hedging and pricing the exposure faced by conventional fossil fuel generators required to accept RE under dispatch priority. We find that the cost of hedging against random RE output under dispatch priority is expensive while increasing RE in liberalized markets, by depressing prices and increasing price volatility, may place greater burden on conventional, dispatchable generators. As support for RE is presented as a public good, we argue that economically efficient RE support mechanisms require recognizing both their direct and indirect costs.
Since 1970 Chile has had a Daylight Saving Time (DST) policy in order to reduce residential electricity consumption in the country. The time change was set for the first time by executive decree in 1970, and since that date it was applied every year without great changes until 2010. Since then, and to date, decrees have been set in order to increase the duration of the DST, arguing that there are reasons associated with energy savings that justify the extension of the measure that has been adopted by the authority in recent years. In the present study the impact of the application of DST in terms of decreased household electricity consumption is analyzed using two complementary methods, one based on a heuristic approach and the other using an econometric model. The results indicate that there is indeed a marginally small reduction in residential electricity consumption, although these results are not homogeneous throughout the country.
Daylight savings time represents a public good with costs and benefits.
We provide the first comprehensive examination of the welfare effects of the spring and autumn transitions for the UK and Germany. Using individual-level data and a regression discontinuity design, we estimate the effect of the transitions on life satisfaction.
Our results show that individuals in both the UK and Germany experience deteriorations in life satisfaction in the first week after the spring transition. We find no effect of the autumn transition. We attribute the negative effect of the spring transition to the reduction in the time endowment and the process of adjusting to the disruption in circadian rhythms. The effects are particularly strong for individuals with young children in the household. We conclude that the higher the shadow price of time, the more difficult is adjustment. Presumably, an increase in flexibility to reallocate time could reduce the welfare loss for individuals with binding time constraints.
This article describes the BMS (Bayesian model sampling) package for R that implements Bayesian model averaging for linear regression models. The package excels in allowing for a variety of prior structures, among them the “binomial-beta” prior on the model space and the so-called “hyper-g” specifications for Zellner's g prior. Furthermore, the BMS package allows the user to specify her own model priors and offers a possibility of subjective inference by setting “prior inclusion probabilities” according to the researcher's beliefs. Furthermore, graphical analysis of results is provided by numerous built-in plot functions of posterior densities, predictive densities and graphical illustrations to compare results under different prior settings. Finally, the package provides full enumeration of the model space for small scale problems as well as two efficient MCMC (Markov chain Monte Carlo) samplers that sort through the model space when the number of potential covariates is large.
Limited evidence suggests that Daylight Saving Time (DST) shifts have a substantial influence on the risk of acute myocardial infarction (AMI). Previous literature, however, lack proper identification necessary to vouch for causal interpretation. We exploit Daylight Saving Time shift using non-parametric regression discontinuity techniques to provide indisputable evidence that this abrupt disturbance does affect incidence of AMI.
Solar energy can enter our energy systems through many doors and windows, mostly as heat and electricity. As costs go down, especially for photovoltaic electricity, the variability of the resource becomes a dominant issue. Interconnections, load management, flexible fossil or hydro power plants and storage capacities of pumped hydro plants combine to make the daily variability manageable, but seasonal variability may be more difficult to address while avoiding overinvestment in solar electricity capacities.
The study aims at quantifying the savings in lighting energy consumption for office buildings in India due to the permanent advancement of Indian standard time from +0530 to +0600 GMT. The study initiates by walk through energy audit to evaluate lighting load and occupancy details for Ahmedabad and Kolkata. This data is used to develop reference models for simulations and determine lighting energy consumption. The time advancement is analyzed by shifting occupancy schedules for office spaces, hence parametric combinations of occupancy schedules with different floor plate sizes, aspect ratios, window wall ratio with lighting controls are analyzed. Results from these models show 6.29% savings in the lighting energy consumption.
The Energy Policy Act of 2005 (Pub. L. No. 109-58; EPAct 2005) amended the Uniform Time Act of 1966 (Pub. L. No. 89-387) to increase the portion of the year that is subject to Daylight Saving Time. (15 U.S.C. 260a note) EPAct 2005 extended the duration of Daylight Saving Time in the spring by changing its start date from the first Sunday in April to the second Sunday in March, and in the fall by changing its end date from the last Sunday in October to the first Sunday in November. (15 U.S.C. 260a note) EPAct 2005 also called for the Department of Energy to evaluate the impact of Extended Daylight Saving Time on energy consumption in the United States and to submit a report to Congress. (15 U.S.C. 260a note) This report presents the results of impacts of Extended Daylight Saving Time on the national energy consumption in the United States. The key findings are: (1) The total electricity savings of Extended Daylight Saving Time were about 1.3 Tera Watt-hour (TWh). This corresponds to 0.5 percent per each day of Extended Daylight Saving Time, or 0.03 percent of electricity consumption over the year. In reference, the total 2007 electricity consumption in the United States was 3,900 TWh. (2) In terms of national primary energy consumption, the electricity savings translate to a reduction of 17 Trillion Btu (TBtu) over the spring and fall Extended Daylight Saving Time periods, or roughly 0.02 percent of total U.S. energy consumption during 2007 of 101,000 TBtu. (3) During Extended Daylight Saving Time, electricity savings generally occurred over a three- to five-hour period in the evening with small increases in usage during the early-morning hours. On a daily percentage basis, electricity savings were slightly greater during the March (spring) extension of Extended Daylight Saving Time than the November (fall) extension. On a regional basis, some southern portions of the United States exhibited slightly smaller impacts of Extended Daylight Saving Time on energy savings compared to the northern regions, a result possibly due to a small, offsetting increase in household air conditioning usage. (4) Changes in national traffic volume and motor gasoline consumption for passenger vehicles in 2007 were determined to be statistically insignificant and therefore, could not be attributed to Extended Daylight Saving Time.
This paper investigates the replicability of three important studies on growth theory uncertainty that employed Bayesian model averaging tools. We compare these results with estimates obtained using alternative, recently developed model averaging techniques. Overall, we successfully replicate all three studies, find that the sign and magnitude of these new estimates are reasonably close to those produced via traditional Bayesian methods and deploy a novel strategy to implement one of the new averaging estimators. Copyright © 2012 John Wiley & Sons, Ltd.
Summer Time (ST) refers to the practice of advancing the clock during the summer (commonly by one hour) in order to adjust it to changes of sunrise and sunset times at that period. Conventionally, ST is expected to accomplish three objectives:
* To reduce electricity consumption during dark evening hours;
* To reduce use of air conditioning systems during the morning.This eff'ect, the result of an additional cool hour, is partially offset by an increased consumption of electricity for lighting during very early morning hours;
* To increase productivity (particularly in the industrial sectors that are not air-conditioned) following an additional cool hour in the morning.
While ST has been adopted in the United States, the Soviet Union (since 1981), and most Western European countries, it has become the focus of public controversy in Israel. This debate has political undertones, for political religious parties claim ST is a hardship for early morning prayers.
In this article we analyze electricity conservation due to ST practiced in Israel in the years 1974, 1975 and 1980. Statistical analysis is performed using data about daily total electricity consumption in Israel during these years and during years when ST was not practiced in Israel. Data had been provided by the Israel Electric Corporation, currently the only provider of electricity in Israel.
Default prior choices fixing Zellner's g are predominant in the Bayesian Model Averaging literature, but tend to concentrate posterior mass on a tiny set of models. The paper demonstrates this supermodel effect and proposes to address it by a hyper-g prior, whose data-dependent shrinkage adapts posterior model distributions to data quality. Analytically, existing work on the hyper-g-prior is complemented by posterior expressions essential to fully Bayesian analysis and to sound numerical implementation. A simulation experiment illustrates the implications for posterior inference. Furthermore, an application to determinants of economic growth identifies several covariates whose robustness differs considerably from previous results.
The paper examines the impact of daylight saving time (DST) on electricity consumption in Jordan. Two types of analysis were done: the first analysis examines the impact of DST on the lighting loads based on a survey study made for residential and commercial sectors. The second examines the impact of DST on the over all electricity generation through analyzing the daily load curves (DLCs) before and after the DST onset and removal in 2000 and 2007. The results show that the application of DST during the year 2000 saves the electricity used for illumination by -0.73% but it increases the overall generation at the onset and removal of DST by 0.5% and 1.4% due to increase in the heating and cooling loads. The analysis of DLCs during the year 2007 shows similar effects as in the year 2000 except during the early morning period at the DST onset where DST decreases the demand during this time. The analysis shows that DST decreases the electricity demand at DST onset by 0.2% and increases it at DST removal by 0.3%. A possible decrease in the electricity consumption may take place if the DST is implemented from April to end of August.
We examine 597 estimates of habit formation reported in 81 published studies. The mean reported strength of habit formation equals 0.4, but the estimates vary widely both within and across studies. We use Bayesian and frequentist model averaging to assign a pattern to this variance while taking into account model uncertainty. Studies employing macro data report consistently larger estimates than micro studies: 0.6 vs. 0.1 on average. The difference remains 0.5 when we control for 30 factors that reflect the context in which researchers obtain their estimates, such as data frequency, geographical coverage, variable definition, estimation approach, and publication characteristics. We also find that evidence for habits strengthens when researchers use lower data frequencies, employ log-linear approximation of the Euler equation, and utilize open-economy DSGE models. Moreover, estimates of habits differ systematically across countries.
Domestic electricity consumers with PV panels have become known as "prosumers"; some of them also have energy storage and we have named the combination "prosumage". The challenges of renewable intermittency could be offset by storing power, and many engineering studies consider the role and value of storage which is properly integrated into the 'smart grid'. Such a system with holistic optimal control may fail to materialise for regulatory, economic, or behavioural reasons. We therefore model the impact of naive prosumage: Households which use storage only to maximise self-consumption of PV, with no consideration of the wider system. We find it is neither economic for arbitrage nor particularly beneficial for shaving peaks and filling troughs in national net demand. The extreme case of renewable self-sufficiency, becoming completely independent of the grid, is still prohibitively expensive in Britain and Germany, and even in a country like Spain with a much better solar resource.
National borders reduce trade, but most estimates of the border effect seem puzzlingly large. We show that major methodological innovations of the last decade combine to shrink the border effect to a one-third reduction in international trade flows worldwide. For the computation we collect 1,271 estimates of the border effect reported in 61 studies, codify 32 aspects of study design that may influence the estimates, and use Bayesian model averaging to take into account model uncertainty in meta-analysis. Our results suggest that methods systematically affect the estimated border effects. Especially important is the level of aggregation, measurement of internal and external distance, control for multilateral resistance, and treatment of zero trade flows. We also find that the magnitude of the border effect is associated with country characteristics, such as size and income.
Daylight Saving Time (DST ) impacts over 1.5 billion people, yet many of its impacts on practicing populations remain uncertain. Exploiting the discrete nature of DST transitions and a 2007 policy change, I estimate the impact of DST on fatal automobile crashes. My results imply that from 2002-2011 the transition into DST caused over 30 deaths at a social cost of $275 million annually. Employing four tests to decompose the aggregate effect into an ambient light or sleep mechanism, I find that shifting ambient light only reallocates fatalities within a day, while sleep deprivation caused by the spring transition increases risk.
A change in UK clock time to harmonise with the EEC is currently under consideration. It has been claimed that one of the possible options: a changeover to Single/Double Summer Time (SDST), would result in substantial savings in UK lighting energy use. In the article, Dr Littlefair analyses the resulting changes in patterns of lighting use, and concludes that the introduction of SDST would in fact lead to extra lighting energy costs.
We exploit daylight saving time (DST) as an exogenous shock to daylight, using both the discontinuous nature of the policy and the 2007 extension of DST, to consider the impact of light on criminal activity. Regression discontinuity estimates show a 7% decrease in robberies following the shift to DST. As expected, effects are largest during the hours directly affected by the shift in daylight. We discuss our findings within the context of criminal decision making and labor supply, and estimate that the 2007 DST extension resulted in $59 million in annual social cost savings from avoided robberies.
We present a meta-regression analysis of the relation between the concentration of carbon dioxide in the atmosphere and changes in global temperature. The relation is captured by "climate sensitivity," which measures the response to a doubling of carbon dioxide concentrations compared to pre-industrial levels. Estimates of climate sensitivity play a crucial role in evaluating the impacts of climate change and constitute one of the most important inputs into the computation of the social cost of carbon, which reflects the socially optimal value of a carbon tax. Climate sensitivity has been estimated by many researchers, but their results vary significantly. We collect 48 estimates from 16 studies and analyze the literature quantitatively. We find evidence for publication selection bias: researchers tend to report preferentially large estimates of climate sensitivity. Corrected for publication bias, the bulk of the literature is consistent with climate sensitivity lying between 1.4 and 2.3 degrees C.
The theoretical literature gives conflicting predictions on how bank competition should affect financial stability, and dozens of researchers have attempted to evaluate the relationship empirically. We collect 598 estimates of the competition-stability nexus reported in 31 studies and analyse the literature using meta-analysis methods. We control for 35 aspects of study design and employ Bayesian model averaging to tackle the resulting model uncertainty. Our findings suggest that the definition of financial stability and bank competition used by researchers influences their results in a systematic way. The choice of data, estimation methodology, and control variables also affects the reported coefficient. We find evidence for moderate publication bias. Taken together, the estimates reported in the literature suggest little interplay between competition and stability, even when corrected for publication bias and potential misspecifications.
We examine potential selective reporting (publication bias) in the literature on the social cost of carbon (SCC) by conducting a meta-analysis of 809 estimates of the SCC reported in 101 studies. Our results indicate that estimates for which the 95% confidence interval includes zero are less likely to be reported than estimates excluding negative values of the SCC, which might create an upward bias in the literature. The evidence for selective reporting is stronger for studies published in peer-reviewed journals than for unpublished papers. We show that the findings are not driven by the asymmetry of the confidence intervals surrounding the SCC and are robust to controlling for various characteristics of study design and to alternative definitions of confidence intervals. Our estimates of the mean reported SCC corrected for the selective reporting bias range between USD 0 and 134 per ton of carbon at 2010 prices for emission year 2015.
I examine 2,735 estimates of the elasticity of intertemporal substitution in consumption (EIS) reported in 169 published studies. The literature shows strong selective reporting: researchers discard negative and insignificant estimates too often, which pulls the mean estimate up by about 0.5. The reporting bias dwarfs the effects of methods, with the exception of the choice between micro and macro data. When I correct the mean for the bias, for macro estimates I get zero, even though the reported t-statistics are on average two. The corrected mean of micro estimates of the EIS for asset holders is around 0.3–0.4. Calibrations greater than 0.8 are inconsistent with the bulk of the empirical evidence.
We collect 2,735 estimates of the elasticity of intertemporal substitution in consumption from 169 published studies that cover 104 countries during different time periods. The estimates vary substantially from country to country, even after controlling for 30 aspects of study design. Our results suggest that income and asset market participation are the most effective factors in explaining the heterogeneity: households in rich countries and countries with high stock market participation substitute a larger fraction of consumption intertemporally in response to changes in expected asset returns. Micro-level studies that focus on sub-samples of rich households or asset holders also find systematically larger values of the elasticity.
In this paper we quantitatively synthesize empirical estimates of the income elasticity of gasoline demand reported in previous studies. The studies cover many countries and report a mean elasticity of 0.28 for the short run and 0.66 for the long run. We show, however, that these mean estimates are biased upwards because of publication bias—the tendency to suppress negative and insignificant estimates of the elasticity. We employ mixed-effects multilevel meta-regression to filter out publication bias from the literature. Our results suggest that the income elasticity of gasoline demand is on average much smaller than reported in previous surveys: the mean corrected for publication bias is 0.1 for the short run and 0.23 for the long run.
In a 1935 paper and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, which is the posterior odds of the null hypothesis when the prior probability on the null is one-half. Although there has been much discussion of Bayesian hypothesis testing in the context of criticism of P-values, less attention has been given to the Bayes factor as a practical tool of applied statistics. In this article we review and discuss the uses of Bayes factors in the context of five scientific applications in genetics, sports, ecology, sociology, and psychology. We emphasize the following points:
Daylight Savings Time (DST) is promoted as a tool to conserve energy. However, ex post reduced form estimates of the effects of DST find no evidence of energy savings and find some evidence of a small increase in energy use. This paper investigates this disconnect using detailed individual time use data to look at the behavioral effects of DST. We study how individuals change their time use in response to the abrupt shift in daylight associated with DST. We leverage two natural experiments to identify the effect of DST on behavior. First, we study periods around the annual shift in daylight induced by moving into and out of DST. Second, we compare activities by time interval before and after the change in DST start dates that occurred in 2007. We find cautious evidence that individuals are shifting potentially energy intensive activities earlier in the day, which is consistent with earlier findings of increased energy usage.
1 . Such proposals have been made in the past, but have not been adopted. In this article we review the ratio- nales for introducing multiple time zones and daylight saving time (DST) and for rejecting both. In the northern hemisphere, DST involves setting clocks ahead by an hour in spring and setting them back by an hour in the fall. In the southern hemisphere, the two adjustments are reversed. We propose an alternative, in effect a year-long DST, which avoids the risks associated with introducing multiple time zones or with bi-annual changes in DST.
Many countries have experimented with daylight saving time (DST) to save energy and to align human activities more closely to the daily cycle of light and darkness. Using a novel methodology, we estimate the year-round energy savings to be obtained from advancing Indian Standard Time (IST), from the introduction of DST, and from dividing the country into two time zones. We find that the option of advancing IST consistently saves more energy than the corresponding DST option, which in turn saves more energy than the corresponding time zones option. This is because the energy benefits of advancing IST accrue for the entire year throughout the country, whereas the benefits of DST are confined to summer months and the benefits of two time zones are largely in the lower energy consuming eastern region. We recommend advancing IST by half-hour to being six hours ahead of UTC. This confers the advantages of DST and time zones without their disadvantages and is forecast to save more than 2billionkWh of electricity every year during evening peaks that are difficult to supply. While these results are India-specific, similar exercises would be useful to many other countries.
The voluminous empirical research on horizontal productivity spillovers from foreign investors to domestic firms has yielded mixed results. In this paper, we collect 1,205 estimates of horizontal spillovers from the literature and examine which factors influence spillover magnitude. To identify the most important determinants of spillovers among 43 collected variables, we employ Bayesian model averaging. Our results suggest that horizontal spillovers are on average zero, but that their sign and magnitude depend systematically on the characteristics of the domestic economy and foreign investors. The most important determinants are the technology gap between domestic and foreign firms and the ownership structure in investment projects. Foreign investors who form joint ventures with domestic firms and who come from countries with a modest technology edge create the largest benefits for the domestic economy.
In this article we conduct a large quantitative survey of the literature on horizontal and vertical spillovers from foreign direct investment (FDI). We create a unique database of spillover estimates for each country examined in the literature. Next, we estimate the average effect corrected for publication selection bias (the preferential selection of positive and significant estimates for publication). Our results suggest that an average reported estimate of backward spillovers is statistically significant. Publication selection is evident only among studies published in peer-reviewed journals, and only among the estimates that authors consider most important. Authors with small data sets engage in more publication selection. The intensity of selection in the literature decreases over time, which supports the economics-research-cycle hypothesis.
One of the most frequently examined statistical relationships in energy economics has been the price elasticity of gasoline demand. We conduct a quantitative survey of the estimates of elasticity reported for various countries around the world. Our meta-analysis indicates that the literature suffers from publication selection bias: insignificant or positive estimates of the price elasticity are rarely reported, although implausibly large negative estimates are reported regularly. In consequence, the average published estimates of both short- and long-run elasticities are exaggerated twofold. Using mixed-effects multilevel meta-regression, we show that after correction for publication bias the average long-run elasticity reaches −0.31 and the average short-run elasticity only −0.09.
Summer Time is a convention in which clocks are uniformly set one hour or more ahead of standard time to provide more daylight in the evenings during late spring, summer, and early fall. The main purpose of Summer Time is to make better use of daylight so that it more closely corresponds to our normal daily activities and thus saves energy. Japan is currently not observing Summer Time. This study thus investigated the feasibility of the energy saving potential of Summer Time/Double Summer Time from the perspective of household lighting in Japan and the optimum implementation period. The study found that both the Summer Time and Double Summer Time could reduce household lighting energy consumption, while the magnitude of energy saving potential of Double Summer Time is higher compared to Summer Time. It was also indicated that April–September is the optimum implementation period of Summer Time/Double Summer Time in Japan, from the perspective of household lighting. In terms of geographical location, under Double Summer Time, the household lighting energy saving ratio of the northern Japan regions is higher compared to the southern region. However, under Summer Time, the energy saving ratio of the southern Japan region is significantly higher.
This study is an evaluation of the effect of using or not using daylight saving time on a residential building's HVAC and lighting energy consumption. Daylight saving time is the practice of shifting clock time ahead by one hour. The well-verified and robust hour-by-hour simulation code DOE-2.1 E is used to predict a residence's annual energy consumption at 224 locations in the US. The quantities tracked are annual electrical energy use, electrical cost, natural gas quantity, natural gas cost and total energy cost. The house used in the study is an existing structure in Lawrence, KS, and its actual characteristics, operation schedules and utility bills are used in the preparation of the energy model. The results show that for this residence, which is somewhat typical of US houses, total energy consumption is just slightly increased on average when summer daylight saving time is used instead of standard time year-round. Other combinations of standard and daylight saving time are also examined.
Most of the developed countries in the world use Daylight Saving Time (DST) as an energy conservation method. This study focuses on the effects of DST on electrical lighting in the buildings in Turkey. Turkey might adjust its daylight saving time to decrease energy consumption. For this purpose, five scenarios are considered and compared to status quo. The scenario with a 30-minute forward shift to single DST from April to October, stands out as the best solution to conserve electricity across the entire country. The results of the study show that maximum saving is obtained in this scenario by at least 0.7% on the consumption of lighting electricity.
It does not necessarily represent the views of the Energy Commission or the State of California. The Energy Commission, the State of California, its employees, contractors and subcontractors make no warrant, express or implied, and assume no legal liability for the information in this paper; nor does any party represent that the uses of this information will not infringe upon privately owned rights. This paper has not been approved or disapproved by the California Energy Commission nor has the California Energy Commission passed upon the accuracy or adequacy of the information in this paper. This paper has not been approved or disapproved by the full Commission.
Abstract There is growing concern and mounting evidence of selectivity in empirical economics. Most empirical economic literatures have a truncated distribution of results. The aim of this paper is to explore the link between publication selectivity and theory contests. This link is confirmed through the analysis of 87 distinct empirical economics literatures, involving more than three and a half thousand separate empirical studies, using objective measures of both selectivity and contests. Our meta–meta-analysis shows that publication selection is widespread, but not universal. It distorts scientific inference with potentially adverse effects on policy making, but competition and debate between rival theories reduces this selectivity and thereby improves economic inference.
In the last decade, more than 100 researchers have examined productivity spillovers from foreign affiliates to local firms in upstream or downstream sectors. Yet results vary broadly across methods and countries. To examine these vertical spillovers in a systematic way, we collected 3626 estimates of spillovers and reviewed the literature quantitatively. Our meta-analysis indicates that model misspecifications reduce the reported estimates and journals select relatively large estimates for publication. No selection, however, was found for working papers. Taking these biases into consideration, the average spillover to suppliers is economically significant, whereas the spillover to buyers is statistically significant but small. Greater spillovers are received by countries that have underdeveloped financial systems and are open to international trade. Greater spillovers are generated by investors who come from distant countries and have only a slight technological edge over local firms.Highlights► We meta-analyze the estimates of spillovers from FDI. ► The average backward spillover is large. ► The average forward and horizontal spillovers are negligible. ► Larger spillovers are generated by investors from distant countries.
This paper examines the impact of daylight saving time (DST) on electricity consumption in southern Norway and Sweden. As DST was implemented in both the countries in 1980, we do not have a clear counterfactual in the form of a control period to identify the impact of DST directly with before and after or with and without analysis. This problem in the study is resolved by using "equivalent day normalization technique" to identify the impact of DST. The difference-in-difference (DID) average treatment effects model suggests an annual reduction of at least 1.0 percent in electricity consumption for both Norway and Sweden due to DST. The average annual electricity consumption reduction corresponding to DST effects equals 519 and 882Â GWh for southern Norway and Sweden, resulting in an annual financial saving of 16.1 million Euros and 30.1 million Euros, respectively. The distribution of treatment effects across different hours of the day indicates a small but significant reduction in electricity consumption during the morning and a steep decline during the evening hours in both countries.
We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. We examine the effect of a variety of prior assumptions on the inference concerning model size, posterior inclusion probabilities of regressors and on predictive performance. We illustrate these issues in the context of cross-country growth regressions using three datasets with 41-67 potential drivers of growth and 72-93 observations. Finally, we recommend priors for use in this and related contexts. Copyright © 2009 John Wiley & Sons, Ltd.
Load Management (LM) is an alternative to meet the increasing peak demand of electricity. The Daylight Saving Time (DST) is one of the options of LM. The implementation of DST is a common practice in many developed countries. Bangladesh Power System (BPS) has recently implemented DST to reduce its unmanageable increasing demand. However, the effectiveness of this option of LM has not yet been evaluated. This paper develops a technique to quantify the effect of DST on a power system. The paper also presents the application of the technique in BPS.
Energy conservation policies for the residential sector are evaluated by a model that simulates city-scale energy consumption in the residential sector by considering the diversity of household and building types. In this model, all the households in the city are classified into 380 categories based on the household and building type. The energy consumption for each household category is simulated by the dynamic energy simulation model, which includes an energy use schedule model and a heating and cooling load calculation model. Since the energy usage of each appliance is simulated for every 5 min according to the occupants’ energy usage activity, this model can evaluate not only the energy conservation measures by improving the buildings and appliances but also the measures that involve changing the occupants’ activities. The accuracy of the model is verified by comparing its results with the statistical and the measured data on Osaka City, Japan. Various types of energy conservation measures planned by the Japanese government for the residential sector are simulated and their effects on Osaka City are evaluated quantitatively. The future effects of these combined measures on the energy consumption are also predicted.
The principal reason for introducing (and extending) daylight saving time (DST) was, and still is, projected energy savings, particularly for electric lighting. This paper presents a literature review concerning the effects of DST on energy use. Simple estimates suggest a reduction in national electricity use of around 0.5%, as a result of residential lighting reduction. Several studies have demonstrated effects of this size based on more complex simulations or on measured data. However, there are just as many studies that suggest no effect, and some studies suggest overall energy penalties, particularly if gasoline consumption is accounted for. There is general consensus that DST does contribute to an evening reduction in peak demand for electricity, though this may be offset by an increase in the morning. Nevertheless, the basic patterns of energy use, and the energy efficiency of buildings and equipment have changed since many of these studies were conducted. Therefore, we recommend that future energy policy decisions regarding changes to DST be preceded by high-quality research based on detailed analysis of prevailing energy use, and behaviours and systems that affect energy use. This would be timely, given the extension to DST underway in North America in 2007.
In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior. In particular, ‘diffuse’ priors on model-specific parameters can lead to quite unexpected consequences. Here we focus on the practically relevant situation where we need to entertain a (large) number of sampling models and we have (or wish to use) little or no subjective prior information. We aim at providing an ‘automatic’ or ‘benchmark’ prior structure that can be used in such cases. We focus on the normal linear regression model with uncertainty in the choice of regressors. We propose a partly non-informative prior structure related to a natural conjugate g-prior specification, where the amount of subjective information requested from the user is limited to the choice of a single scalar hyperparameter g0j. The consequences of different choices for g0j are examined. We investigate theoretical properties, such as consistency of the implied Bayesian procedure. Links with classical information criteria are provided. More importantly, we examine the finite sample implications of several choices of g0j in a simulation study. The use of the MC3 algorithm of Madigan and York (Int. Stat. Rev. 63 (1995) 215), combined with efficient coding in Fortran, makes it feasible to conduct large simulations. In addition to posterior criteria, we shall also compare the predictive performance of different priors. A classic example concerning the economics of crime will also be provided and contrasted with results in the literature. The main findings of the paper will lead us to propose a ‘benchmark’ prior specification in a linear regression context with model uncertainty.
The focus of this work is an investigation of the effect of prevailing time regime on energy consumption. In particular we perform analysis demonstrating potential energy savings which could be obtained were Great Britain to maintain daylight savings time (DST) over winter, instead of reverting to Greenwich mean time (GMT). We review the literature on the effect of DST on energy consumption and show that this indicates a justification for considering the issue. Our headline result is in agreement with many related studies in that advancing the clock by an hour in winter would lead to energy savings of at least 0.3% of daily demand in Great Britain. In deriving this result we have adopted methodologies currently used in load prediction, in particular Support Vector Regression, to estimate energy demand on a half-hourly basis.Corresponding cost savings are found to be higher (due to the nonlinear increase of costs) and we find them to be on the order of 0.6% over the months considered. In terms of environmental impact we find the saving to be approximately equivalent to 450,000 ton of CO2. In deriving these results we adopt a conservative approach such that we consider them lower bounds on any true savings.
The magnitude of the value of a statistical life (VSL) is critical to the evaluation of many health and safety initiatives. To date, the large and rigorous VSL research literature has not explicitly accommodated publication selectivity bias (i.e., the reduced probability that insignificant or negative VSL values are reported). This study demonstrates that doing so is essential. For studies that employ hedonic wage equations to estimate VSL, correction for selection bias reduces the average value of a statistical life by 70-80%. Our meta-regression analysis also identifies several sources for the wide heterogeneity found among reported VSL e