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Questions related to Applied Economics
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Can economic growth occur in the short term? If the answer is no, what is the reason behind economic growth not occurring in the short term and occurring only in the long term?
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There are two main sources of economic growth: growth in the size of the workforce and growth in the productivity (output per hour worked) of that workforce. Either can increase the overall size of the economy, but only strong productivity growth can increase per capita GDP and income. The temporal aspect of economic growth, dear Mohammed Asseel , is therefore based on the realization of dynamic efficiency, i.e. dynamic and efficient allocation of
  • Natural resources.
  • Human resources.
  • Technology.
  • Capital formation.
  • Dynamic efficiency is influenced by, for example, research and development, investment in human and non-human capital and technological change. It is when all resources are allocated efficiently over time, and the rate of innovation is at the optimum level, which leads to falling long run average costs.
  • In terms of the: Golden Rule capital stock in the Solow Growth Model
  • https://www.csus.edu/indiv/v/vangaasbeckk/courses/100a/sup/goldenrule.pdf
  • rapid economic growth can occur in short-term or time, in the sense of a speedy human learning curve for value creation (learning that pays).
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I would like to test whether the general relationship between the number of years of education and the wage is linear, exponential, etc. Or in other words, does going from 1 year to 2 years of education have the same impact on wages as going from 10 to 11. I want a general assessment for the world and not for a specific country.
I got standardized data from surveys on several countries and multiple times (since 2000). My idea is to build a multilevel mixed-effects model, with a fixed effect for the number of years of education and random effects for the country, the year of the survey and other covariates (age, sex, etc.). I’m not so used to this type of model: do you think it makes sense? Is this the most appropriate specification of the model for my needs?
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https://d-nb.info/1212378199/34
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What are examples of social policy programmes that have increased the fertility rate in society, reduced the scale of family poverty and effectively acted and slowed down significantly the progressive process of long-term changes in the demographic structure of society known as the ageing process?
Unfortunately, not all such social policies have worked effectively. For example, in the country where I operate, such a social policy programme whose official strategic goal was to counteract the rapidly declining birth rate of children and the rapidly progressing process of demographic changes in society defined as ageing since the end of the 20th century in Poland is the Family 500 Plus Programme, introduced in 2016. Apart from this, the key ongoing objective of this programme was to improve the material status of children, financially support families raising children and reduce the scale of family poverty in Poland. In the first years of the programme's operation, i.e. from 2016 onwards, this programme became one of the important factors of economic growth. The Family 500 Plus programme consists of a monthly non-refundable transfer of PLN 500 for each child in the family. I have described the strategic goals of this programme as a key element of long-term, i.e. on a multi-year scale, socio-economic policy planning and implementation in my published articles and monograph chapters on my profile of this Research Gate portal. I invite you to join me for research collaboration on this issue. However, the Family 500 Plus programme has already been in place for several years. The design and introduction of this programme drew on models of similar programmes operating for years in other countries in Europe. this programme was introduced in Poland in 2016. It is now already 2023. In 2022, the level of child births in Poland was the lowest in more than half a century, so clearly this programme is completely failing to meet the strategic goals that were set out when this programme was introduced. These strategic objectives, in addition to reducing the scale of poverty among families with many children in Poland, were to significantly increase the fertility rate in society and thus counteract the progressive ageing of the population. This programme has been implemented by the PIS government in Poland for almost eight years. In connection with the fact that, according to political scientists, the introduction of this social policy programme helped the PIS political party to win the parliamentary elections in 2015 and 2019 and the formation of the government by this party, so for years there have been considerations as to whether the introduction of this social policy programme, i.e. the programme of financial support for families in Poland, was related not to the issue of long-term shaping of social and economic policy in Poland but to the issue of winning the parliamentary elections. In view of the above, the current goals of the Family 500 Plus Programme have been achieved, while the strategic goals, unfortunately, have not.
In view of the above, I would like to address the following question to the esteemed community of scientists and researchers:
What are the examples of social policy programmes that have increased the fertility rate in the society, reduced the scale of family poverty and effectively acted and slowed down to a large extent the progressive process of long-term changes in the demographic structure of the society defined as the process of ageing?
What do you think about this topic?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
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As far as ageing is caused by increasing (hopefully healthy) life expectancy, there is no reason for policies to slow it down. In many developing countries, ageing may be a desirable development. It makes no sense to have a compensating population growth in order to grow-out of ageing. There are enough people (one may even say: too many people) in the world. Every more contributes to mor environmental damage. A slight popultation shrinkage could mean that we are better off - even with a non-growing or shrinking GDP (because we Ias a society) dispose of considerable material wealth created in the past. Economists should foreget Neoclassical growth theories and try to find concepts for non-growing economies.
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I have two questions. (1) I want to generate estimates of gross output at industry-by-district level based on total sales value of business establishments. What additions/deductions do I need to make to the total sales value to arrive at the gross output figure for an establishment or industry. (2) Once I have arrived at gross output for industry, then I need to generate estimates of aggregate gross output for the whole economy. To arrive at aggregate gross output for the whole economy, do I simply need to take sum of gross output of all establishments, or there is a particular methodology for this purpose.
I am doing this for Zambian economy. Actually the problem is that when I take the aggregate sum of total sales value of all establishments in the economy, and compare it with an estimate of aggregate gross output published by a government report, I find my aggregate sum of total sales value exceeding the aggregate gross output in the publication. It exceeds by a huge difference.   So, what could be possible reasons? Is it that I miss out any deductions? or there could be some other reasons?
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Why is Keynesian theory not considered as a theory of economic growth? Although it simply suggests that income, which Keynesian theory assumes equals output, can be changed by increasing effective aggregate demand, it all takes the case from the demand side rather than from the supply side.
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In practice, since resources need capital to find and develop them, since technological improvement can be applied to production only via capital investment, since entrepreneurial skills act only through investments, and since an increased labor supply is rela­tively independent of short-run economic considerations, the only viable way to economic growth as rise in living standards is through increased saving and investment. Either more and better resources can be found, or more and better people can be born, or technology is improved, or the capital goods structure is lengthened and capital multiplied. In the Austrian or psychological view of human economic action, what brings about improvement comes not by economic growth or by stability, but through economic transformation that is guided by the freedom of private initiative within an open market system, i.e. instead of its fixation on economic growth and stability, a non-interventionist system would favor the space that is given for the individual to demonstrate and actively pursue his preferences.
The current interventionist approaches , in contrast, put the individual under a modern kind of serfdom where "output" or rather "expenditure" becomes the statistical criteria.
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It is your mind that matters economically, as much or more than your mouth or hands. In the long run, the most important economic effect of population size and growth is the contribution of additional people to our stock of useful knowledge.
Julian Simon
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I am estimating the Boone-indicator by using difference GMM. However modified the basic equation by including year dummies and the interaction of Ln(MC) with year dummies time ( t=1 to T) as explanatory variables instead of Ln(MC) only to estimate yearly Boone-indicator. I have got the estimate for the whole sample period but I am now confused how to get it for each year.
The equation is attached.
Thank you.
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Your question regarding Boone the indicator is a little bit ambiguous. if you are calculating the Boone indicator for a time span, say (i.e., 2010-2020), then Dynamic difference or SYS-GMM perfectly make sense. However, since the Boone indicator is a yearly measure, therefore, you have to run a simple OLS model for each year to obtain the coefficient value of lnMC.
The command for STATA in my example can be "reg lny lnmc if year==2010"
repeat this regression for each year to obtain the coefficient value of lnMC (i.e., this value is your Boone indicator). Hope it would help you.
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Hello. I am a phd student and I have been asked to analyze an article based on economic theory and in connection with business continuity management. But I am having a hard time finding such articles. If anyone has experience with these topics and can help. Any suggestions will be appreciated.
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To add to Sridhar Chakravarthi Mulakaluri 's answer, from a classical economic perspective, the first perspective of handling disruptions would be short-run economic solutions, while the second is characteristic of long-run interventions. In a classic, over-simplified two factor theory of the firm, short-run economic interventions may be more relatable to labour economics (on the basis the variation of capital elements is less likely to be an option) whereas, in the long-run, one can consider more capital intensive solutions. Using this as a framework, I would start looking for papers across both economics and business continuity that discuss such factors. There will be overlap, but it may not be explicit.
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I want to do a descriptive analysis using the World Values Survey dataset which has an N=1200. However, even thought I have searched a lot, I haven't found the methodology or a tool to calculate the sample size I need to get meaningful comparisons when I cross variables. For example, I want to know how many observations do I need in every category if I want to compare the social position attributed to the elderly over sex AND over ethnic group. That is (exemplying even more), the difference between the black vs indigenous women in my variable of interest. What if I have 150 observations in black women? Is that enough? How to set the threshold?
Expressing my gratitude in advance,
Santiago.
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When you divide a sample into subgroups, your maximum power is where the groups are of equal size. So the first step is to calculate power two samples of 600.
Where the groups are of unequal size, power goes down compared with the ideal case of a 50:50 split. With a 60:40 split, the effective sample is reduced by only 4%, but as you get to 80:20, the reduction is 36% and at 90:10 it's 64%. So with a 90:10 split your power is what you would have with a sample that was 64% smaller split 50:50 between the groups.
Effective sample size calculations are very simple. The ideal sample is 0·5 x 0·5, which is 0·25. A 30:70 sample is 0·3 x 0·7 which is 0·21, which is 12% lower than 0·25. etc.
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Hello
I am doing some reading in the field of neo-liberalism and stumbled across the terms welfare liberalism. When trying to find definitions I came across the term social liberalism. Please excuse my ignorance but are there any recommendations for papers/chapters explaining the terms?
Thanks
Susan
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Thanks for your help Burke.
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I have GDP and MVA data and though the MVA is stationary, the GDP is non stationary even after log-transformation followed by de-trend followed by differencing. I want to build a VAR/VEC model for ln(GDP) and ln(MVA) but this data has been haunting me for past 3 days. I also tried both method of differencing i.e linear regression detrend and direct difference but nothing seems to work.
Also, they(ln GDP and ln MVA) satisfy the cointegration test, the trends are very similar. But for VAR/VEC I will need them to be I(1) which is not the case. Any suggestions on how to handle this data will be highly appreciated!
I have attached the snapshot of the data and also the data itself.
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If the time series is short, you can can be converted the data into quarterly data, it will give better results
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Does anyone know any paper related to the economics of touring by rock bands? I know it is likely to get gross figures for concerts but I wonder why they still keep touring even when many of them are billionaires (see Rolling Stones)
Any help is appreciated
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I think you might find Alan Krueger's work useful:
- (book) Rockonomics: A Backstage Tour of What the Music Industry Can Teach Us about Economics and Life
Literature on the impact of rock shows exists, but it might not be what you're looking for (since it's not really about heavy metal). Anyway, here's some links:
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I am trying to run a regression of cobb douglas function:
The problem that my dataset capture the firm at a point of time,
So I have a dataset over the period 1988-2012.
Each firm appears one time!
(I cannot define if it is a panel/time series/cross section..)
I want to find the effect of labor, capital on value added.
I have information on intermediate input.
I use two methods Olley& pakes, levinsohn-patrin.
But Stata is always telling me that there is no observations!
my command:
levpet lvalue, free(labour) proxy(intermediate_input) capital(capital) valueadded reps(250)
Why the command is not working and telling that there is no observations?
(Is this due the fact that each firm appear only one time in the data?)
(If yes, what is the possible corrections for simultanety and selection bias in this data?)
Thanks in advance for your help,
Mina
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I agree with anton
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I co- authored a study of a born global or rather born regional IT firm in the process of internationalisation during the Covid 19 pandemic. The firm quickly adapted to the new reality. My question is that if you think that firms in other industries show a similar behavioral pattern? Or do you think the handling of the pandemic varies between industries? The article can be found as full text here :
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Dear Dr Henrik G.S. Arvidsson , Really interesting information. Thanks a lot for that and initiating a discussion on this. Warm regards Yoganandan
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I am interested to know about the difference between 1st and 2nd and 3rd generation panel data techniques.....
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First generation panel data analysis often assume cross sectional independence, i.e the shock to a variable in a country will not have any effect on the other countries variables. However, as a result of globalization and other related cross nation interlinks, it is apparent that a problem in country A can affect country B. Most of the conventional panel analysis like fixed effect, Random effect, Panel ols, among others fall into this category. In order to correct the bias in the estimate of 1st generational panel analysis, the 2nd generational panel analysis was invented. This methods appropriately incorporate the cross sectional dependence in the modeling. This includes methods like ccemg, cs-ardl, cup-FM and so on..
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Happy New Year fills your heart with happiness, Happy New Year to all friends and pioneers of this platform as well as to the whole world, what do you expect the general features of the new year, especially with the pandemic?
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Dear Mutasem Z. Bani-Fwaz, happy new year to you and to the whole RG Community. My Regards
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Usually we use the two terms interchangeably in our articles but whether is there any technical difference between them?
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I guess the difference is in the words implication Vs recommendation. Implication is the outcome result following your analysis, while recomendation is what you proposed or your choice of outcome to follow.
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Dear RG colleagues,
I applied OLS regression analysis and usually, I report CUSUM and CUSUMSQ stability tests. But this time, I have to report more stability tests and I also included heteroscedasticity tests. My question is, are these two enough, or should I incorporate additional stability tests of coefficients or residuals? What are the most popular stability tests of the models? Thank you beforehand.
Best
Ibrahim
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In standard applied econometric modelling practice, it is advisable to run as much diagnostic tests as possible to optimise model performance/estimates, but being cautious about running tests that are applicable/relevant.
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I have got the time series data (results) of mi, tc, pech and sech. How to elucidate these? How to correlate these with real world meanings?
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@Ahmed Mohamed Habib Sir, thank you.
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i have companies data as dependent variable for 10 years across 200 companies (all companies from one country only) whereas the macro economic variables are for 10 years as independent variable  (again the same one country). 
can this analysis be completed using panel data technique? if yes, then how the data will be arranged first because the macro variables are same for each company in sample for 10 years. or is there any alternative to study the influence of macro variables on company's financial ratios.
can someone please help with my analysis? 
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My question is:
I have data of 7 life insurance companies for 10 years and i included 9 independent variables & 1 dependent variable. So how could i arrange this data in excel sheet i.e in table form so that i could apply certain statistical techniques in eviews/spss.????
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There are several quantitative studies (mainly linear regressions) that describe the behavior of deforestation in Brazil. However, I do not find dynamic systems that relate economic factors and deforestation. DSGE models could provide a theoretical basis for the explanation of deforestation in Brazil. They would also allow forecasts to be made and avoid recurring problems found in linear models (endogeneity, heteroscedasticity, etc.). But why isn't there a DSGE model that considers deforestation?
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Thank you very much
Luis Rivera , about IPEA's exercise, it was one of the first to use deforestation instead of greenhouse gas emissions. The reason is that deforestation data is easier to calculate and more accessible. It even mentions that models with two countries, and considering greenhouse gases, were only recently estimated.
Perhaps this is the explanation of why I was unable to find publications involving DSGE and deforestation.
I also think that David de la Croix is ​​correct. In Brazil the main cause of deforestation is investment in new pasture areas. So, maybe deforestation should be analyzed in the long run.
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The administrative traditions in most Latin American countries are more prone to bureaucratic practices concerned in the documentary record of
normative procedures ("compliance") rather than the concrete outputs (or outcomes) of public hospitals as a result of appropriate public health policies.
This situation is mainly understood as one of the consequences of the Iberian colonization heritage, that set up the transmission of customs
of extensive bodies of elaborated written uniform laws and rules for governments in this world region (*).
In my opinion, these administrative practices are somewhat reluctant to introduce M&E (monitoring and evaluation) technics based on academic research work and quantitative-qualitative data collection.
At least for the argentine case, this situation can be verified from the observation of the quotidian work of the External Audit Institutions
-or SAI's- at a federal government level, as well as at subnational levels of government (Courts of Accounts, General Audits, etc.).
In contrast, countries whose public sectors are subject to "performance auditing" or "program evaluations" by their respectives SAI's -such as the Anglo-American administrative traditions or most OECD countries- have not only implemented "compliance audit" methods that verify legal compliance or financial statements, but also applies evaluation methods -supported by INTOSAI guidelines- that audit outcomes of public health policies (**).
(*) Painter, M. and Peters, G. "Tradition and Public Administration", Painter and Peters (Eds.) 2010. Palgrave MacMillan UK.
(**) Barzelay, M. "Central Auditing Institutions and Performance Auditing: A Comparative Analysis of Organizational Strategies in the OECD". Gov.: An Int. Journ. of Pol. and Adm., V.10, No.3, July 1997 (pp.235-260).
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Please Go To This Link:
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Thinking about food crop production this year, will there the surplus or shortage as a result of the global pandemic?
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COVID 19 has no direct impact on the crops, but it diverge concentration of farmers towrds its care due to low income and fear.
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I have a well endowed database with almost 29 0000 observations and I want to make an analysis with more than 50 variables. What are the problems that can arise from this situation? Can the model be overfitted? If it is possible, why?
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Yes. Your model can be overfitted. You can think of overfitting in several ways, but let us take two different avenues. First, number of relevant variables. Imagine that the truly correct model has only 30 of the total of 50 variables that you happen to have. Whatever method you use to identify the correct variables in your model can lead you to "false discoveries". This is closely related to the type I error in statistical inference. You can be very strict with the type I error, but this will never be zero. So, you are admitting the possibility of false discoveries. These false discoveries have more chances to occur, the more variables and transformations of variables you try over the same sample. You mention that you have 50 variables...but what about using the squares of these variables, or logs of them or product of pairwise combinations of them. The more combinations you try over the same sample, the more likely is that you end up with false disvoveries: variables that are not in the model...but your statistical method is unable to detect that they are not....
Second, imagine that the true share of variance that can be explained in your model is 50%. So, this is the best R2 you can get if you could identify the correct model. Now, because you are trying to find the correct variables using the same sample over and over again, you end up with a sample R2 of 75%. You again have an overfitting issue induced by the data mining process.
Large N helps but a lot of the overfitting problem relies on the repeated use of the same sample to find a correct model.
This is a key topic....hope it helps!
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As from theoretical construct and empirical literature, i have found that tax base is defined as - tax revenue divided by tax rates. if the standard data on tax rates are not readily available, than how we can estimate tax base for central and state level ?? What could be the other suitable proxies for measurement of tax base ??
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Hi, Yadawananda Neog. I usually consult these following webpages in studying effective tax rates:
I hope they would be helpful for you.
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Does adding renewable energy sources to smart grid change the price?
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Closed loop elastic demand control by dynamic energy pricing in smart grids
Broadcasting of dynamic energy price signals for consumer's demand response programs (agents) is an effective and feasible way for demand side load management in future smart grids. Particularly, under fluctuating generation conditions of distributed renewable sources, automated and online market management strategies based on dynamic pricing are necessary for persistently conservation of energy balance and reducing the risk of instant energy shortages in the smart grids. This study presents a control theoretic energy market management approach based on closed loop elastic demand control scheme by means of dynamic price signal broadcasting. A PI controller structure is used to regulate energy price signals for demand response agents of smart grid community. Thus, total energy demand can be governed to respond fluctuation of renewable energy generation. To illustrate an application, a renewable energy integrated microgrid management scenario was studied numerically. A first order dynamic system model with a piecewise linear price-demand response is used to represent overall demand elasticity of the microgrid and a renewable energy microgrid simulation scenario is developed in Matlab/Simulink simulation environment. Simulation of 90 MWh peak demand market demonstrate that the closed loop dynamic energy pricing can be useful to control the elastic demand for tracing fluctuating generation of renewable energy sources. It is concluded that dynamic energy pricing can be useful medium for energy demand control.
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We are trying to value the co-benefit for a REDD+ strategy in Costa Rica, and that involved do the valuate the ecosystem services at national level
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many of the studies are rather technical in nature and do not go into qualitative considerations of achieving good environmental services.
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if we want to build a performance index depends on a set variables. what's the indicators can be used to measure economic performance and whats the desired values to these variables?
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Paul: The three main economic variables you should track are: Inflation, Unemployment, and GDP Growth rate.
The desired values depend on the country. In the United States, the desired values are: Inflation = 2%, Unemployment rate = 5%, and DP Growth rate = 3%
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Dear colleagues,
Participation in a conference is a way to promote research. This enriching experience also helps to become known in academia, to learn about one of the facets of the teaching-research profession and to establish important professional relationships.
Thus, we are pleased to inform you of the launch of the call for papers of the 2nd International Symposium on Statistics and Econometrics (CISEM) 2019, to be held on May 3, 4 and 5, 2019 in Mahdia (Tunisia).
This symposium is organized by the Research Unit in Applied Economics and Simulation (Unité de Recherche en Economie Appliquée et Simulation) and the Scientific and Cultural Association at the Faculty of Economics and Management of Mahdia (Association Scientifique et Culturelle à la faculté des Sciences économique et de gestion de Mahdia) in collaboration with several research structures, national and international universities and international organizations such as French Society of Statistics (Société Française de Statistique) https://www.sfds.asso.fr/fr/activites/562-manifestations_parrainees/ and the Statistical Society of Canada https://ssc.ca/fr/congres
The objective of the symposium is to offer a platform for the discussion of recent developments in statistics, applied mathematics and applied econometrics through the meeting of researchers and doctoral students from different disciplines, the presentation, as well as the discussion of the results of their research and their empirical studies.
We are also pleased to invite you to submit your scientific contributions to the following address: cisem2019@gmail.com.
For more information, visit the conference website: http://cisem2019.asc-fsegma.com/
Looking forward to hearing from you and, hopefully, welcoming you to Mahdia.
Best regards,
Abdeljelil Farhat, Ph.D
Full Professor of Statistics, Econometrics and Quantitative Methods
Director of the Research Unit EAS-Mahdia
Faculty of Economics and Management of Mahdia,
Monastir University, Tunisia;
Telephone: 216-21-164-045;
216-99-646-702
Fax: 216-73-683-190
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Dear Ayman and Elma,
We thank you for your interest
in the 2nd International Symposium on Statistics and Econometrics (CISEM) 2019, to be held on May 3, 4 and 5, 2019 in Mahdia (Tunisia).
We are counting on your presence and your contribution. Do not hesitate to contact me for more information.
Regards,
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Hi,
I'm studying the effect of water pricing for industrial users. There is a well-stablished literature for demand functions for residential consumers, but not for industrial consumers.
The assumed inverse demand function of water is of the form A-Bq. What is the proper way of estimating the parameter values (A and B) of this function? All I found in literatures is the price elasticity of demand.
Thanks for your contribution.
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Sorry for the typo, demand function* and marginal revenue*
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The evolution of world economy is strongly conditioned by the financial system, and specially by the behaviour of the numerous and diverse financial markets (stocks, money market, forex, interbank, bonds, derivatives, commodities, etc.). For this reason, financial variables determine consumption, investment, foreign trade and public spending.
I propose this question, in which I would like to know if you agree or consider open some additional points of view of the economy that may condition new economic crises. Thank you.
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I agree with Carmelo Ferlito note, that I suppose is quite near to the Schumpeterian analysis you may find in Business Cycles: the structural economic dynamics is always at the beginning of a major financial crisis. In a certain sense it is also at the beginning of the 2008 financial crisis, that - IMHO - cannot be understood without considering the ICT technological revolutions in the '90s which have addressed increasing amount of liquidity in financial markets.
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I am working on a project linking parental homeownership to happiness score of their children and trying to figure out economic reasons whether to treat parental homeownership as endogenous or exogenous in my empirical model.
I have seen a number of studies on individual homeownership and their happiness score not treating homeownership as endogenous but some studies on parental homeownership and academic achievement of their children treating parental homeownership as endogenous. However, they just say that parents who own homes might be different in their characteristics and also in the way they raise their children. I still feel there needs to be more explanation to this if to treat as endogenous. Or should I just treat it as exogenous?
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It is accurately addressed research issue. Ownership of immovable property creates responsibility and set benchmark for performance comparison from generation to generation. Rest need to assess
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In an open and globalized economy and considering the financial markets influence, I ask for your collaboration, from a theoretical point of view, to propose economics postulates that can reduce social inequality and give better solutions to complex problems such as sustainable growth and the equitable distribution of wealth. Thank you in advance.
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Sustainable development and their social and economic dimensions
Social development commitments are:
  Eradicate absolute poverty by a date to be determined by each country.
  Support full employment as one of the basic policy objectives.
  Promote social integration based on the promotion and protection of all human rights.
  Achieve equality and equity between women and men.
  Accelerated development in Africa Least developed countries.
  Ensure that social development goals are included in structural adjustment programs.
  Creating an "economic, political, social, cultural and legal environment that enables people to achieve social development".
  Enabling everyone to have equal access to education and primary health care.
  Strengthening cooperation for social development through the United Nations
Economic development is generally defined as the process through which a comprehensive and sustained change occurs, accompanied by an increase in real average income, an improvement in income distribution for the poor, an improvement in the quality of life and a change in the structure of production. According to this definition, development contains a number of elements, the most important of which are:
  Inclusiveness, development is a comprehensive change that involves not only economic, but also cultural, political and social.
  The continuous increase in real income average long period of time, this suggests that development is a long-term process.
  An improvement in the distribution of income in favor of the poor and the alleviation of poverty.
  Need to improve the quality of goods and services provided to individuals
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Hi,
I am currently calculating energy intensities of household, industrial, commercial, transportation, and other sectors (in MJ/GDP unit). I have the data of energy consumption for those sectors. However, I have no idea how to calculate the share/contribution of each sector to GDP. GDP data are mostly by economic sectors, which omits the household sector contribution
Can anyone help me?
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Usually, governments have a lot of data on National Accounts, reflected on the GDP segmentation. Also, some branches ( agricultural, industrial, business, etc) have their own statistics which might reflect their share on the GDP. My advise: Do some ¨in the field¨research with a clear conceptualization of the end-use of the data available, this will save you time and money.
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Hi guys, I might be silly to ask this question. Here is the situation I am facing and any suggestion would be appreciated.
I am writing my first serious research paper in economics. At the beginning, I simply wanted to replicate a similar study using Chinese data set (as a way to get familiar with my data set). During this process, I realize that I can do something more than a replication but that would mean a change of research direction. I have already devoted a lot to the current topic and got all the statistical tests done by now. My tutor thinks it is better to finish this one and get a publication first (although a replication would not be published in a good journal).
However, I am now in my first year of Ph.D study and do not have too much pressure about publication. So I kind of think that keeping on with the current topic would be a waste of time (especially because I have already got familiar with the data set).
I do not worry much about my situation now, since either way would work for me. But this affair alarms me that similar situations can happen in the future. I would be gratitude if you guys can share some experience or advice about the following two questions:
1. When I find another topic more worthwhile, when should I stop the current study and change a direction, and when should I continue on the current topic?
2. If I hold different views about the above question with my coauthor, what should we do?
Thanks in advance.
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Forget the matter for a few (say 15) days.
Then autometically you will get the solution from yourself.
It is tested by me several times.
Thanks.
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Hermann Bondi used k calculus to model special relativity. Sarrus and Rameaux supposed scaling based on dimension modeled the lower breathing rates of larger animals for species with constant body temperature. Scale applies in economics and cities as Geoffrey West describes in his recent book, Scale. Galaxies scale. Environments scale. Populations scale. Concepts scale. Networks scale. Scale is built into fractals. Perhaps the scaling of efficient energy distribution underlies all. But what underlies that scaling? Is scaling built into creation, is it the pulse of the universe? If so, how? Is scaling a result of the expansion of the universe or the result of dark energy? Is scaling due to the metronomic iteration of photons flying through space? What elemental aspect of the universe leads to the pervasiveness of scaling?
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Scaling applies when physical laws have the form of power laws. Now many physica laws can be expressed in that form at least in some range of their variables. In that "range of scales" we may be able to produce a description in terms of scaling. Fractals became popular, because they provided a paradigm of scaling laws. (In an ideal fractal, scaling applies at all scales. In the real world, we usually have it only between a minimum and a maximum scale.)
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Dear Asma Madouri, do you know that how to carry out this test now? I also need to do this test for my paper.
Thank you!
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Dear everyone, In light of current happenings in developing economies, are the most contemporary issues in applied economics that economist must seek solutions to. what robust research must applied economist embark in pursuit of finding solutions to societal problems? Could this be in the areas of poverty, heath, education, finance and or some recent concern to developing economies. if "Yes" what are these most pressing issues that need immediate solutions? All your comments and suggestions are Warmly welcome and thanking you in advance.
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I think one of the primary research topics in developing countries is "How to encourage sustained economic growth? " In other words, what factors are most closely related to economic growth in a poor economy? (Microfinance?) What can the government do to encourage economic growth?
A related topic is "How to reduce poverty?"
Still another question is "How to reduce government corruption?"
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How to explain the phenomenon of increase in price a commodity in the period of three generations, in a simple and layman’s language.
For example,
When my grandfather was in his childhood, we could buy a chocolate for 5 paisa and my son buys a chocolate for 5 rupees. (1 rupee equals to 100 paisa). Mathematically, it means there was 100 times increase in the price of a chocolate.
How do we understand the increase in price by 100 times?
Does it mean that inflation was increased by 100 times during this period? Or
At that time of my grandfather, economic activity was limited and so money circulation was also limited and accordingly level of the purchasing power of the people was very low.
Or any other better explanation from the layman’s viewpoint.
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On the one hand, when talking about a good number of times of price increase during two-three generations time isn’t about just inflation, or it is, but just indirectly. Inflation is price increase on the short time only and about this it produces its specific effects – nearly no effect now, when just finding it and making a few calculus about.
Then, it might be about inflation, but about some repeated inflation during a good while. Inflation equally keeps its money depreciation face. But on the one hand this issue isn’t simple at all, on the other tempting a full explanation about is nearly a teaching adventure, if not an assumed failure. All I can here say is mentioning that I already recommended our Srikanth Potharla colleague’s question started – all the more he isn’t an economist.
Back to my tempted answer to his question, at least let us see that there isn’t just inflation to talk about, plus, inflation itself isn’t quite a disaster either. The idea is that today all money (national currencies) do depreciate continuously (not only rupee) – and, once more, this isn’t any problem; the problem arises only when such depreciation is a shock one (from today to tomorrow and during the year). Actually, money depreciation, at least when moderate, is a symptom of money, a symptom without disease.
And now let me interrupt this description – for here coming back below – for explaining that such depreciation has a beginning – and this is (just take it as my view, only) or was the fall of the former gold standard for universal money, i.e. it occurred in the interwar period and after some other self-destruction precedents of that system. Or, recall how gold standard was simply like: prices were rather lowering, inflation was as rare and low due to being caused by some gold production rare booms in the late 19th century.
It is reasonable understanding that it was the gold metal resource at that time rising its individual price against the other commodities' ones. But not only – i.e. there were equally other causes of money appreciation at that time, e.g. much more market competition, less monopolies, no State’s involvement in economy by public spending and monetary policy ruling, less investments and economic development, less unemployment threat…
Gold standard has got bankrupted for its own causes and just after international money disorder came up. Roughly, since 1971 (fall of the new post-gold international monetary system) gold was fully out of any monetary system and since 1985 (i.e. the ‘La Platza-Louvre’ international conference) the non-gold monetary system regained its own order. Plus, the international dimension of all national currencies strengthens once more – but while in the national systems monetary policies do the same.
And now let us see the basic difference between gold standard and the today national scale monetary environment for understanding why and how at that time money was appreciating and today it is exactly the opposite. Gold standard meant no monetary policy – money supply was exactly the State’s gold reserves and the same State wasn’t controlling this money supply. Plus, the (small) minting house was all the State had, i.e. but this as rather its engagement for keeping the currency unit’s price.
On the contrary, when no gold standard any longer the State uses the central bank – and this is much larger than minting house; often including it – and this is really for controlling money supply. The last is just the first one that continuously increases for its own priorities – actually the State’s monetary policy purposes --, but of course, as a premise for the next future money’s continuous depreciation. Mr. Thernik is here very right – it is money supply rising that directly makes money depreciation. But, once more, this is either no any essential bad in this, or not the single money depreciation factor.
And finally, let me enumerate some of other money depreciation causes, except for the above debated aspects:
· market competition falling, more monopolies and oligopolies;
· investments rising, even crowding, while inflation factor;
· public spending rising, while inflation factor either,
· wages (and salaries) continuously rising, never falling, while the so-called ‘labour market’ isn’t quite a real market segment and labour is both costs and market demand for goods; and both boost inflation at the same;
· pressure on natural resources rising, as well, pushing up costs together with wages rising;
· international market prices’ behaviour since this market was demonstrated as no perfect competition either; then influences on domestic prices ;
· the fact that inflation is priory agreed by policy makers against unemployment or even against too much transparency about what happened to real wages and general life standard…
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Hello. I am actually doing a study for the relationship of foreign trade with economic growth in Albania. My data is yearly, ranging from 1993 to 2016 (Export, Import, GDP). I am using log form (lnexport,lnimport,lnGDP) to conduct the study (lnGDP is the dependent variable). Unit Root test(ADF) indicates the series are stationary at first difference [I(1)].
Regarding lag length, 'Lag Length Criteria' chooses as optimal lag 1 when max lag is 1; lag 2 when max lag is 2; lag 1 when max lag is 3 and lag 4 when max lag is 4 (SIC and AIC criterion). Judging from my intuition lag length should be 1, as the data is yearly.
When I open the differenced series as VAR the coefficients after estimation appear to be insignificant. When I do the Johansen Cointegration test (data in levels) it shows 2 cointegrating equations in the long run. After that I check VECM (in levels) and the coefficients still appear insignifcant. I also ran a Granger Causality test (differenced data) which shows no causality in any direction. 
What can I do now? Does that mean the series need to have more data? 
I would be very grateful for any suggestions regarding my study, which is actually very important to me, as I need it for my thesis. I am also attaching the results for a better understanding (*removed after edit).
EDIT: Thank you everyone for your suggestions. I tried to use quarterly data and it worked. With optimal lag 7 (according to AIC) there was one cointegrating vector and VECM was successful with the error correction term being negative and significant.  Also the export coefficient sign was positive and the import coefficient was negative (in the long run part of the equation) thus satisfying economic theories. I am attaching the result below.
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An explanation without any theory will likely lead to misspecified equations. A god estimate for such an equation is not a data problem ("weakness of data"). Even if you had a mass of data and, by accident, got good statistical results, these resuts are not acceptable.
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Under what circumstances can GMM be used and what problems of panel regression does it address.
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Thanks a lot Prem for your very insightful answer.
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Hello Everyone! Could any one recommend me better time series model for forecasting gross agricultural production growth with less statistical noise?
I want to indulge ones nation overall agricultural production growth sustainability by using over 10 years panel data.
Could you recommend me the appropriate, straightforward and accurate an econometric model to forecast precisely. Which endogenous and exogenous variables  should be tested for better policy input?
Thank you!
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for time series models, it is vital to have large datasets especially for prediction.for limited datasets you can use ARDLboundmodel.
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I look at the World Bank and found only series from 2011
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Dear Celeste
Penn World Table is a good resource which is used in articles.
Regards
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hi, can i use GMM in unbalanced panel data with N=35 and T=36 ? thank you
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Yes you can use GMM with a time period 2000-2015. In PMG, you can introduce I(0) to measure the short term effect, with the I(1) variables expressed in first differences.
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If one is to use Transparency International rating of a country, for example, for a number of years (let say 5 years is 136, 132, 135 128 130), can these number be used directly and interpreted in terms of higher value for low transparency of that country (since higher number indicate lower rating in Transparency International Rating) or it has to be transformed. If it is to be transformed, into what level(s) will it be transformed. 
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Dear Friend
I use the CPI to calculate the impact on human development in Argentina, and I could use it as a correlation of the development variables, or as an independent varaible against the dependent variable (a development example, poverty)
Thus showing correlation of corruption and development variables, correlation and intensity, and see the impact of corruption on these variables, greetings
It's in my book "Economia de la Corrupcion" at Amazon
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hello,
i am conducting a research regarding the effect of Secondary offering by firms on stock returnes. i have taken 25 different firms from different branches and want to check 5 year monthly returnes using CAR model. i would like to compare the results to U.S market index like s&p 500 or other.
can someone please explain the way for it?
thank you
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Hi Yossi,
First calculate Abnormal Return(AR) using the market model or any other versions of asset pricing models. You may use event study method along with different event windows.
Hope this helps,
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based on the definition..
1. if i use stock price as data input, stock price series should have randomness and no autocorrelation?
2. if i use stock return as data input, stock return series should have stationary(not randomness) and no autocorrelation?
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3. stationarity is not, randomness is.
Stationarity of stock returns does not provide any support or rejection of EMH.
Randomness is certainly relevant. If you find some pattern in stock returns, then they are not random, and you reject EMH. Autocorrelation is just one particular type of non-randomness. If there is significant autocorrelation in returns, returns are not random, and you reject EMH.
4. stationarity of stock returns does not help you to identify any evidence for or against EMH. Randomness of stock returns helps you to identify whether there is evidence against EMH. Stock returns should be stationary. Whether returns are random, it depends, it is what people are often testing.
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I am running a difference in difference regression to assess the early impact of minimum wage introduced in 2015 on satisfaction of workers. I actually have data from 2010 to 2015 but the panel is unbalanced since some individual seem to be missing in different years. Do you suggest that i should focus on just 2014 and 2015 waves using the same individuals (balanced data) to run the regression and I should consider also the other years before the introduction of the minimum wage?
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Hi David, I think you need the years before the minimum wage too because with DID, you are not only interested in groups with and without but also their differences with respect to time.
My only challenge is whether you distinctively have two groups -- those who benefited from the minimum wage and those who did not.
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Dear all,
This seems trivial but I need to ask from those with more research experience: is it right to transform a "rate" variable such as the interest rates, growth rates and inflation rates into natural logarithms?
Some studies do while some don't with each "School" giving different arguments.
Please what is the right thing to do?
Thanks!
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Hello, Hubert. It seems you are working hard and successfully.
As for taking logarithm of rates, there seems to be another reason. If you are led to take rates, it indicates that the time series you are observing is a multiplicative series. I say this in comparison to additive series.
Here is a rough idea. Let X(t) be a series of random variables, mutually independent and having two first moments (i.e. averages and variations). Then
Y(t) = Y(t-1)*X(t) ∀ t ∈ Z
is a multiplicative stochastic series and
U(t) = U(t-1) + X(t) ∀ t ∈ Z
is an additive stochastic series. For example, the amount of IOU, GDP of a nation, the price index can be considered as multiplicative series.
It is a well known theorem that a multiplicative series forms a normal distribution, when it is measured by logarithms and by subtracting trends. This theorem is easily derived form the theorem on additive series.
As you see it, taking logarithms is to transform a multiplicative series into an additive series. Many theorems are expressed for additive series and we are more accustomed to additive series than multiplicative series. For this reason, for example, we are more accustomed to take arithmetic average than geometric average. I do not why but it is possible that physical processes are additive rather than multiplicative.
In a multiplicative series, it is more natural to take rates in place of differences, but if you want to use theorems of stochastic process, you are led to take logarithm as it transforms multiplicative series into additive series.
I hope I am clear.
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Many cities and states in the United States are pushing the Minimum wage higher and higher.  Many have a goal of $15 an hour or more.  
As the Minimum wage goes higher and higher, what are the negative consequences (drawbacks)?  
Do you believe their is an Upper-limit to the minimum wage, where the negative effects are greater than the benefits?  Why or why not?
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The issue of the effects of MW on labor market is highly controversial, both in theory (competitive LM model versus monopsony) and in practice (Card & Krueger vs. Neumark & Washer). I think that the empirical consensus is that there are relatively small negative effects of MW on some groups of  low-skilled workers(e.g youth). Most existing studies, however, studied relatively small MW hikes, 20-30%. But what if we double MW in some country, region, or city? And this issue is close to the issue raised by Paul. Unfortunately (or fortunately) such examples of doubling MW are rare. What we found for Russia (https://link.springer.com/article/10.1186%2Fs40175-016-0051-0) is that the effects in fact are not dramatic. We found a very modest decline in youth employment and increase in informal employment as a reaction to MW hike. Of course, it is difficult to extend these conclusions to USA , (e.g., due to different strength of enforcement of MW legislature, tax morale, inflation rate, informal sector, etc) but still this suggest that the 'upper limit' is much higher than may be expected according to classic competitive LM model.
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Dear all,
Please can anyone clarify which is more appropriate to adopt when testing for structural breaks - is it on the dependent variable or on the main explanatory variable?
For instance, if I want to explain income inequality (using the Gini index) via the influence of trade reforms, do I construct the econometric specifications based on break points in the inequality series or the trade series? Although, I think it should be on the explanatory variable, I just need to be sure.
Kindly advise....thank you.
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Thanks Najib, but I have since modified the model. I now have just two variables explaining income inequality. They are domestic credit and per capita GDP. I'm thinking that since a series of financial reforms took place in Nigeria between 1986 and 2009, perhaps the domestic credit should be the break "variable" to consider. Or, I can use the Gregory-Hansen (1996) test result for the model to obtain the probable break dates. What do you think?
Please help if you can....gracias!
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For instance I have a research proposal to be sent to a funding agency, is it necessary to include the cost of the project when I have not started it though I have the estimate of what the cost may be.
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This is a great question!  Thanks for asking.  My experience is that it is good practice to include your best estimate of the cost in the application for a grant.  I understand that it may be a challenge to estimate your cost when you haven't even started any steps in the research process.  However, think of the people who have to approve the grant.  It is extremely helpful to them if you can provide them with a cost estimate.  They may have a limited budget or they may have to answer to their supervisors.  My advice is to include your best and honest estimate of your cost.  
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is it possible to study the causal relationship between the objectives of economic policy (magic square of kaldor), and which model we can use it, and which model we can work by it.
referring to kaldor's article (1971) "Conflicts in National Economic Objectives"
who is the first person who draw the magic square, because in the kaldor's article he didn't explain the objectives within any square.
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Yes, It is possible to study the relationship between objectives of economic policy. Causality can be well judged by the VAR model as Helmi said..
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we are trying to understand the relationship between industrial clusters and innovation in the context of indian manufacturing sector during the post reform period.
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 are you talking about this paper which is published in research policy
Does the knowledge spillover theory of entrepreneurship hold for the region.
this paper explores the relationships in the context of Germany.  we are exploring this kind of relationships in the case of india where uniiversity-industry linkages are comparatively weak. 
can you suggest any research work in the context of developing countries........
thanks and regards
baldev shergill
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In the context of India.I need a variable with quarterly frequency.
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thank you @ arun kumar sir
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arms procurement expenditure in South-Sudan. How oil revenue fuels weapons procurement?. Estimated amount the government of South-Sudan has earned from oil export over the years.
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I agree. Political instability in a oil-revenue earning country is a heady mixture and potent risk. 
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Economics have paied much attention to competition theory and obtained very robust conclusions about firms' decisions and market perfomance. But most of these theory were based on an implicit assumption which is one-tier market. In other word, traditional didn't pay much attention to vertical relationship except vertical integration and vertical control and also didn't form a complete theoretical framewrok. What's the reason? And where can I find some reference about this topic?
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Dear Rob,
American justice is based on common law.  Japanese justice system is based on legislation. The court plays a very narrow part in the conflict settlement. This may make a big difference.  If then, a similar argument can be heard in the legislation process, but in reality such discussion seems rare. (I am not very sure about this. This is only my impression.)
Yoshinori 
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Kindly share materials that will help me understand how to interpret the output of "DASP: Stata modules for distributive analysis".
Thank you.
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Dear Demian Tupac Panigo, thank you for the link. I found the presentation (Abdelkrim Araar, Jean-Yves Duclos and Luis Huesca, 2011) very helpful. Many thanks. Cheers!
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economics development international trade panel data 
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Use PPML-Estimator technique it is equally good for balanced and unbalanced, counters hetro well and large zero in trade data are controlled meaningfully. Moreover it is consistent with international trade.
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In my model, log form of cpi in usd is determined by log form of money supply in myanmar kyats, log form of consumption in myanmar kyats, log form of import in usd. Is this possible? And how could be the interpretation?
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Hi,
Thank you indeed for your good explanation . That means a lot to me
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I am trying to calculate TFP of firm in Cambodia using Enterprise Survey In 2013. As I understand to get TFP, i sum residual and the constant together after I regress log value add on log labour and log capital. This, i think I got logA which ranges from 1 to 14 n it is log TFP. If it is true I can see that value of logTFP and thus TFP is too big, in which I have notice the calculation of the world bank for TFP in developing countries are only around 1 or 2. In this regards, I wonder if there is a certain range for TFP? And whether how I calculated was right?
NOTE: labor = number of full time permanent employees 
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Hello Dr. Makiela, thank you so much for your answer. I am using OLS to calculate TFP since i have only one year cross-sectional data. According to the World Bank, the residual of this production function (Cobb-douglas is assumed) is the TFP. Thus, it takes negative value i think.
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Cyclically adjusted data is used by many countries now a days so that to remove the impact of cyclical fluctuation of business cycle on fiscal deficit.
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I am by no means an expert on the Indian economy; however, I thought the following might be helpful:
When I see cyclically adjusted data it is usually due to seasonality rather than longer-term fluctuations that might be associated with a business cycle or perceptions related to it.  For example, this is especially significant today since it is so close to the Income Tax filing deadline in the US.  Each year, this seasonality influences the monetary flows to the US government.
Some things like the GDP Gap might be useful in a different context because it is heavily influenced by deviations from full employment.
I hope this helps.
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I would like to estimate the total costs of getting a community to do something. Which is the best method to use in this estimation? Especially non monetary costs e.g time, in a community or group I am likely to spend more time than in individual decision making situation.
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Regular cost-benefit analisys can be used, but concerning family labor do not value it at market price unless the member of the family left a job to work at the farm or community. The cost of that labor is the diference betwen monetary income and monetary expenses
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Can we use "Price level of the physical capital stock, price level of USA in 2011=1" as a proxy of cost or price of physical capital stock in the panel data research? What's about discount rate, which one is better?
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Hi Shahzad,
Ideally we use logarithmic of the stock price to fulfill the stationarity assumption. As for the discount rate, the treasury bills rate is popularly used as the risk free rate in asset pricing test. Best Regards - Jasman
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We have to carry out an empirical panel analysis of economic growth and see differences in factors of growth between groups of heterogeneous countries. As in economic growth much of the attention focuses on the form of the growth model estimated (factors included and the possibility of omitted factors) and this has to be a keystone of our paper, we would like to justify our election very well. To do so we need to use a strong, published and accepted model as baseline-model. What model (paper) would you recommend? Thank you very much.
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Thank you all for your valuable suggestions.
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based on empirical research and not only in theory
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Hola, Loliana. Le puede echar un vistazo a este trabajo de David Green. Creo que le será útil. Saludos.
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Dear All,
I am currently using the Blinder-Oaxaca decomposition in one of my papers. However, in one of my decompositions I have the "difference" between two groups that is not significant and the "endowments" and "coefficient" components that are significant.
How should I interpret that?
Thank you for your time
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Hello. The key point in your estimations is that there are no significant differences between both groups. I think going beyond could not have sense. Is the same as having a no significant coefficient in an estimation, to deep in the analysis of the relationship has not sense. Good luck with your work, Keou.
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I think that the most difficult part of modeling an economic agent-based model is to extract literature and sound micromechanisms to support agents decision-making.
I have a simple model that have the reasoning described below.
I was wondering whether anybody could help suggest alternative micromechanisms and accompanying literature to support the suggestions
This is a work in progress, I appreciatte the feedback.
Thanks
1. Firms
a. Decision on wages: given by earlier results, i.e., profits in the last quarter
b. Decision on prices: given by level of stock (Bergmann, 1974, Blinder, 1984)
c. Decision on hiring and firing: given by combination of profits and level of stocks
d. Decision on quantity: deterministic, given by capacity of production (pool of workers)
2. Workers
a. Decision on salary accepting: taken (given by the firm)
b. Decision on quantity to buy: parameter of propensity to consume (exogenous)
3. Markets
a. Matching goods: price is given, families buy by minimum price (101 economics) or minimum distance from shop
b. Matching labor: salary is given, firms paying higher salaries chooses first, workers are ranked according to qualification (Boudreau, 2010)
c. Matching housing: houses prices given by characteristics and location (typical hedonic pricing equations (textbook), DiPasquale and Wheaton, 1996); price of location evolves with incremental government investments; families are ranked by savings available and houses by prices; family with less resources bid for the cheapest houses and so on until no more houses or families on lists. Final prices (may be) the average of offered and asked prices [at the moment prices are given by houses characteristics only]
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Ola Bernardo! 
For firms: 
It could be worthy considering sticky wages: Heckel, T., Le Bihan, H., & Montornès, J. (2008). Sticky wages: evidence from quarterly microeconomic data.
For pricing it would be nice to consider competition, see for example: Klenow, P. J., & Malin, B. A. (2010). Microeconomic evidence on price-setting (No. w15826). National Bureau of Economic Research.
For workers: 
About accepting the salary you could think about reservation wages: Yellen, J. (1995). Efficiency wage models of unemployment. In Essential Readings in Economics (pp. 280-289). Macmillan Education UK.
For markets:
Your matching mechanisms for the markets sound sophisticated enough, I can only think about including/testing product differentiation: Abdel-Rahman, H. M. (1988). Product differentiation, monopolistic competition and city size. Regional Science and Urban Economics, 18(1), 69-86.
* About housing, it could be interesting to introduce beliefs about the future evolution of prices, and use the model to study housing bubbles (see the preliminary paper attached). 
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I i have applied NG Perron's modified tests to my timer series data. But when I tried to interpret test statistics I saw that, the decision given by MZa and MAzt contradicts with MSB and MPT.
Is there an assumption which I should know, that would cause this diversion
Thanks..
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I advice you use ADF,  DFGLS, PP and KPSS and to forget that test because his results are difficult to understand.
Good luck
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Hello Experts! I'm Using stata to practicing the TFP decomposition for a panel data which has 34 industries, following the method published in Kumbhakar's book 2015.
The TFP change is defined as:
TFP= TC+TEC+Scale efficiency+Allocational Efficiency
Applying the sf_predict command with the marginal option after ml max, stata saved bc and jlms efficiency indexes and come with the average marginal effect of technical efficiency.
in the book, the TEC(technical efficiency change) was defined as the saved result of the marginal effect of U, but I've noticed in the panel data all industries has predicted as the same TEC. even though the U(efficiency index) by industries was different.
does this method assumes all industries has the same technical efficiency change, or this command only save the average marginal effect? How can I predict the Technical Efficiency Change for each industry?
Hope this figure can tell better than my poor writing.
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Dear Kang, I am afraid that I am not familar yet with the TFP based on marginal effect.  But, it seems that your are using two approaches to estimate the same.
JLMS (inefficiency and efficiency estimation via Jondrow et al. 1982)  and BC (inefficiency and then efficiency via Battese and Coelli 1992 and 1995 assuming you have environmental variables). For example, another approach would be to use confidence interval for inefficiencies via Horrace and Schmidt (1996) approach (see Belotti et all paper).
So my highlight is that I am not sure if you are doing the same thing twice. Another issue could be that you may not have such variability across the years. I would advise you to estimate first the inefficiency and efficiency with for example BC92, predict them and then to see if these change significantly across the time (eta parameter). I wish this helps. Ane
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I have panel data of 757 companies for the period of 2006-2013. I am using FE2SLS and EC2SLS for estimations. If I use time dummies for all years my results are not good. And, if I use time dummies for 2008,2009 and 2010 (financial crisis) my results improved. Can I go for second model ?
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First, I don't know what exactly you estimate. Thus, my answer might be preliminary. I have 2 observations about your problem. First, I would be sceptical about your model specifications if the inclusion of all time dummies leads to very different results than the inclusion of a subset of time dummies. Second, of course you can add any number of time dummies you want (at least in standard panel specifications, careful with GLS though). This is just a matter of Interpretation. In your case, you Interpret the years 2008, 2009 and 2010 against the average of the other observed years. I would prefer a post-crises Dummy, ie, a variable that equals one if you are after the crises, because this is more easily interpreted. If you don't have a proper Interpretation, your referee probably will not support your specification.
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I use system-GMM to assess the effects of financial conditions on macroeconomic performances. But I face to some doubts. Some of my regressors are non-stationary. So, how can I deal with?
- Can I just first-differentiate non-stationary regressors in my system-GMM? Do results remain relevant in terms of interpretation?
- Can I just use system-GMM with non-stationary regressors at level? Because it seems System-GMM is consistent with persistent variables?
- Or, is there another way to deal with this issue ?
Best regards!
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You have not stated the format of your panel database. Do you have small T and large N or you have large T and small N. When you have N>T, you do need to worry about stationarity of the variables because the problem of autocorrelation much less severe and can be corrected by controlling for time-specific effects (by including time dummies). So, in a system GMM framework you will go ahead and run your regressions, but you will need to control for time-specific effects. However, when T>N, then you will have to worry about stationarity and the estimation would be much more demanding. You will need to ask yourself, why do we perform unit root tests? It is because we want to establish whether the estimates are susceptible to a spurious regression. So, after unit root testing, we should perform cointergration tests to establish whether there is a LR relationship between the dependent variable and the predictors. If the cointegration hypothesis can not be rejected, then we proceed with untransformed variables. However, where cointegation is rejected, there is need to consider an error correction model. 
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Hello everyone.  I want to know what countries do to attract FDI after relief of sanctions. Thanks a lot. 
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Dear Abbasi, 
I found out visa facilitation to boost FDI in general. Other variables have also been investigated accordingly. 
I enclose the paper for your attention.
Best regards,
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I run a model on physical capital per woker, in which variable of gross fixed capital formation shows negative sign. Can anyone guide me according to theory for this neagtive sign? 
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Respected Sir Hameed Rafiee!
My model is about to evalaute the impact of some main and also some conditioning varaibles on physical capital per worker. As physical capital is my dependent variable and that is calculating by prepetual inventory method than divided by labor force. Including some other control variables one of the varaible is gross fixed capital formation (GFCF) as %of GDP.  When i run the model the coefficient of (GFCF) shows negative sign. My question is about the theoretical reason of such negative sign for dependent varaible
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Hello fellow researchers,
As noted in the title, i'm wondering if there has been any work done in game theory for two interdependent industries. That is, firm B needs qA to produce qB and Firm A needs qB to produce qA. For simplicity, let's assume firms are monopolists in their respective industries (attached).
Your feedback is highly appreciated.
Nabeel
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I think this paper ...
Boucekkine, Raouf, Jacek B. Krawczyk, and Thomas Vallee. "Towards an understanding of tradeoffs between regional wealth, tightness of a common environmental constraint and the sharing rules." Journal of Economic Dynamics and Control 34.9 (2010): 1813-1835.
which deals with two regions rather than industries, can answer some of your questions. Please let me know how you go.
Good luck,
Jacek 
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I have a time series data on shipping accident and offshore drilling accident economic losses as  X1 and X2  respectively, as independent variables and Y = GDP of the maritime sub-sector as dependent variable.
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The ideal way to do this would be with a general equilibrium model, but that's quite costly. Second-best would be to use an input-output model. Take a look at this article on the impact of occupational injury on the economy. Your regression would have far too much noise to be credible. The Impact of Occupational Injury Reduction on the U.S. Economy, E Zaloshnja, T Miller, G Waehrer, American Journal of Industrial Medicine, 49:9, 719-727, 2006.