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The Phenomenon of Lag in Application of the Measures of Monetary Policy
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This paper discusses the theoretical aspect of the phenomenon of lag in the application of the measures of monetary policy. Monetary and fiscal policy faces the phenomenon of lag. One of the controversial and pressing questions of monetary policy is the nature and length of lag between the application of the measures of monetary policy and the effects on macroeconomic aggregates. While the monetary strategy points to several possible reasons for the lag, there is no general agreement on the length of the lag. The study of the phenomenon of lag imposes two questions: what does the lag of the application of monetary processes and policy imply and why are the asset holders not capable of immediately adjusting their portfolios at the time of disbalance? There are two categories of lag known in economic literature: the inside lag (which encompasses the recognition of the problem and the implementation of measures) and the outside lag (which encompasses the reaction of macroeconomic aggregates to the applied measures of monetary policy). The paper descriptively notes the different identifications of time lag and provides schematic representations of the effects of the observed phenomenon.
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... Policy lags are generally understood as unavoidable time delays. While there may exist several possible reasons for a lag, there is no general agreement on its length (18). This can be explained by the high sensitivity of the lagged and baseline exposure terms and also the implication of time-varying confounding variables in the models (19). ...
IntroductionEvaluating the potential effects of non-pharmaceutical interventions on COVID-19 dynamics is challenging and controversially discussed in the literature. The reasons are manifold, and some of them are as follows. First, interventions are strongly correlated, making a specific contribution difficult to disentangle; second, time trends (including SARS-CoV-2 variants, vaccination coverage and seasonality) influence the potential effects; third, interventions influence the different populations and dynamics with a time delay.Methods
In this article, we apply a distributed lag linear model on COVID-19 data from Germany from January 2020 to June 2022 to study intensity and lag time effects on the number of hospital patients and the number of prevalent intensive care patients diagnosed with polymerase chain reaction tests. We further discuss how the findings depend on the complexity of accounting for the seasonal trends.Results and discussionOur findings show that the first reducing effect of non-pharmaceutical interventions on the number of prevalent intensive care patients before vaccination can be expected not before a time lag of 5 days; the main effect is after a time lag of 10–15 days. In general, we denote that the number of hospital and prevalent intensive care patients decrease with an increase in the overall non-pharmaceutical interventions intensity with a time lag of 9 and 10 days. Finally, we emphasize a clear interpretation of the findings noting that a causal conclusion is challenging due to the lack of a suitable experimental study design.
... Furthermore, Sims and Zha (1999) and Giordano et al. (2007) pointed out that error bands corresponding to 0.68 probability is often more useful than 0.95 bands since they provide a more precise estimate of the true coverage probability. 14 Data on GDP are collected quarterly and are typically released two months after the end of a quarter (Jovanovski and Muric, 2011). 15 The elasticity of net revenue to GDP (e Y nr ) is estimated as the product of the elasticity of revenue to GDP (e Y r ) and the average ratio of revenue over net revenue (r=nr) in the period examined. ...
This article aims to estimate fiscal multipliers in Italy by assessing the effect of an increase in government expenditure and taxes on the Gross Domestic Product (GDP). By applying structural vector autoregressive modelling to Italian quarterly data for the 1995–2019 period, I show that expansionary fiscal policies produce positive effects on the GDP level. Estimated spending multipliers are higher than 1, and when government investment and consumption are compared, findings show that government investment has a larger effect on GDP than government consumption. Estimated tax multipliers are lower than 1, and tax-based policies are less effective in stimulating GDP than expenditure-based fiscal plans. My findings strongly support the Keynesian perspective and indicate that Italy should increase public investments considerably in order to foster economic growth.
... Policy lags are generally understood as unavoidable time delays. While there may exist several possible reasons for a lag, there is no general agreement on its length (Jovanovski and Muric, 2011). Similar time lags have been noticed during the COVID-19 outbreak. ...
The unprecedented challenges caused by the COVID-19 pandemic demand timely action. However, due to the complex nature of policy making, a lag may exist between the time a problem is recognized and the time a policy has its impact on a system. To understand this lag and to expedite decision making, this study proposes a change point detection framework using likelihood ratio, regression structure and a Bayesian change point detection method. The objective is to quantify the time lag effect reflected in transportation systems when authorities take action in response to the COVID-19 pandemic. Using travel patterns as an indicator of policy effectiveness, the length of policy lag and magnitude of policy impacts on the road system, mass transit, and micromobility are investigated through the case studies of New York City (NYC), and Seattle—two U.S. cities significantly affected by COVID-19. The quantitative findings show that the National declaration of emergency had no policy lag while stay-at-home and reopening policies had a lead effect on mobility. The magnitude of impact largely depended on the land use and sociodemographic characteristics of the area, as well as the type of transportation system. Our framework effectively identifies abrupt and significant changes in different transportation systems and can be utilized in understanding dynamics related to COVID-19. Knowing the possible length of lag from enactment of social distancing and reopening policies to heterogeneous impacts on different cities and transportation systems will aid transportation agencies with resource allocation decisions and systems readiness in the event of future outbreaks.
... In a similar vein, the lag between the commitment and disbursement of aid can also be taken into consideration, which further widens when the donor faces temporal shocks. Temporal lags could also arise due to institutional inefficiencies or to lags regarding information flow, recognition, or implementation (Jovanovski & Muric, 2011). As a result, the budget planning of the recipient government is affected, especially when aid forms a significant chunk of its GDP. ...
This study investigates the link between fungibility and international aid effectiveness by combining quantitative and qualitative methods; using state-of-the-art statistical analysis with in-depth interviews with key stakeholders, it provides deeper insights into fungibility and its drivers. It uses a different starting point than most studies on fungibility, namely that fungibility might actually be quite positive to achieve Sustainable Development Goals (SDGs). It contributes empirically to the debate on aid effectiveness and fungibility with respect to Pakistan, one of the largest recipients of Official Development Aid (ODA) over the past decades. Findings suggest that there is an inverted U-shaped relationship between aid inflows and government development expenditures. While development expenditures of the government rise initially with aid inflows, expenditures actually decline with higher aid levels. Looking at the interviews for the case of Pakistan, we can conclude that this higher level of fungibility with higher aid inflows might actually be good news for recipient countries, as valid reasons to reallocate the original allocations also emerged. Our main policy implication is that donors and recipient governments should collaborate more on the allocation and redistribution of funds to ensure successful progress towards the SDGs with minimal loss of scarce resources.
... Prior to any fiscal action, authorities have to identify the problem and this identification requires gathering and analysing economic data which are not available instantaneously because they are released only infrequently (information delays). For example, data on GDP are collected quarterly and are released about two months after the end of a quarter ( Jovanovski and Muric, 2011 ). Hence, information on prolonged change in GDP will be available only two months after the end of the second quarter. ...
This paper aims to estimate fiscal multipliers in eleven Eurozone countries. To do this, we make use of yearly data provided by the OECD for the 1970–2016 period. By using the Local Projections approach on a panel dataset and considering different model specifications, we estimate the magnitude assumed by fiscal multipliers in order to assess whether an increase in government investment generates a ‘Keynesian effect’ on the level of the GDP. Our findings suggest that fiscal multipliers tend to be larger than one and an increase in public investment engenders a permanent and persistent effect on the level of output also when fiscal foresights are considered. Additional model specifications suggest that government investment fiscal multipliers are lower when the post-crisis period is excluded by our sample and are larger in Southern countries than Northern ones.
... Prior to any fiscal action, authorities have to identify the problem and this identification requires gathering and analysing economic data which are not available instantaneously because they are released only infrequently (information delays). For example, data on GDP are collected quarterly and are released about two months after the end of a quarter (Jovanovski and Muric, 2011). Hence, information on prolonged change in GDP will be available only two months after the end of the second quarter. ...
This paper aims to estimate fiscal multipliers in eleven Eurozone countries. To do this, we make use of yearly data provided by the OECD for the 1970–2016 period. By using the Local Projections approach on a panel dataset and considering different model specifications, we estimate the magnitude assumed by fiscal multipliers in order to assess whether an increase in government investment generates a ‘Keynesian effect’ on the level of the GDP. Our findings suggest that fiscal multipliers tend to be larger than one and an increase in public investment engenders a permanent and persistent effect on the level of output. Additional model specifications suggest that government investment fiscal multipliers are lower when the post-crisis period is excluded by our sample and are
larger in Southern countries than Northern ones.
The Covid-19 pandemic has had major implications for government administration. Policymakers set policies for handling Covid-19 as a priority agenda at this time. However, these measures have reduced other problems such as stunting which still requires government attention. This article explores policy management of stunting by the local government amid the Covid-19 pandemic with the West Sumatra province case. The findings in the field, show that the implementation of stunting prevention policies is not easy considering the powerlessness caused by budget refocusing and overlapping authorities between institutions. Meanwhile, the meaninglessness is indicated by the low level of public support for the handling of stunting. This is exacerbated by a bureaucratic culture that is slow to implement policies, including in managing stunting-related programs during the Covid-19 crisis. So that there is alienation or what we call as alienation in the bureaucracy in implementing stunting prevention policies. In the end, the management of stunting policies during the Covid-19 pandemic should receive strong support from all involved parties.
This paper investigates the determinants of economic growth from both a theoretical and an empirical perspective. The paper combines the supermultiplier model of growth with the Neo-Schumpeterian framework that emphasises the entrepreneurial role of the state. We aim to detect the macroeconomic effect generated by alternative fiscal policies: generic ones and more directed ‘mission-oriented’ ones. Using an SVAR model for the US economy for the 1947–2018 period, we show that mission-oriented policies produce a larger positive effect on GDP (fiscal multiplier) and on private investment in R&D (crowd-in effect) than the one generated by more generic public expenditures.
Recent literature has established that development assistance is often fungible and that this is undesirable. In line with current efforts to ‘decolonise development studies’, we critically reflect on the underlying assumptions of this line of thinking. We establish a framework that differentiates between potential positive and negative fungibility. We hypothesise that recipient governments can redirect their own funds and achieve positive fungibility, if (1) the marginal value added in the alternative target sector/region is higher; (2) equity concerns are adequately addressed when other sectors/regions are supported; and (3) temporal delay helps to cushion instability of aid flows. There are indications that this positive fungibility might be quite prevalent. Future fungibility research should therefore no longer assume that fungibility is in itself undesirable.
There is an emerging consensus that money can be largely ignored in making monetary policy decisions. Rudebusch and Svensson [1999, Policy Rules and Inflation Targeting. In Taylor, J.B. (Ed.), Monetary Policy Rules. University of Chicago Press, Chicago, 203–246; 2002, Eurosystem Monetary Targeting: Lessons from US Data. European Economic Review 46, 417–442] provide some empirical support for this view. We reconsider the role of money and find that money is not redundant. More specifically, there is a significant statistical relationship between lagged values of money and the output gap, even when lagged values of real interest rates and lagged values of the output gap are accounted for. We also find that inside and outside money provide significant information in predicting movements in the output gap.
This paper examines the transmission of monetary policy in Canada. It emphasizes the transmission through interest rates and the exchange rate rather than through changes in monetary aggregates and provides empirical evidence on the strength of these channels using a highly aggregated structural model. Implications of these structural equations for the dynamic effects of monetary policy are explored through a simulation analysis.
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Although the concept of monetary policy lag has historical roots deep in the monetary economics literature, relatively little attention has been paid to the idea. In this paper, we build on Svensson’s (1997) inflation targeting framework by explicitly taking into account the lagged effect of monetary policy and characterize the optimal monetary policy reaction function both in the absence and in the presence of the zero lower bound on the nominal interest rate. We numerically show the function to be more aggressive and more pre-emptive with the lagged effect than without it. We also characterize the long-run stabilization cost to the central bank by explicitly taking into account the lagged effect of monetary policy. It turns out that, in the presence of the zero lower bound constraint, the long-run stabilization cost is higher with the lagged effect than the case without it. This result suggests that the central bank and/or the government should set a relatively high inflation target when confronted with a relatively long monetary policy lag. This can be interpreted as another justification for targeting a positive inflation rate in the long-run.
This paper presents evidence on the monetary transmission process in the euro area, based on macroeconomic data and on micro data on banks. According to the estimations of macro vector autoregression and macroeconometric models, a monetary policy tightening significantly reduces output and--after a time lag--also prices. The effect on output is temporary, while that on prices is permanent. Clear patterns of significant asymmetries in the monetary policy effects across countries do not emerge. The estimations based on micro data on banks show that the main factor that determines the average bank's response to monetary policy is its degree of liquidity: the lower its share of liquid assets in total assets, the more strongly does a bank reduce its lending in response to a monetary tightening. Bank size does not emerge as an important factor for a bank's reaction to monetary policy. These results hold for virtually all member countries of the European Monetary Union, despite the differences in their banking systems. Copyright 2003, Oxford University Press.