Questions related to Applied Economics
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?
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?
I invite you all to discuss,
Thank you very much,
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?
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.
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.
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.
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,
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?
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.
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!
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,
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 :
I am interested to know about the difference between 1st and 2nd and 3rd generation panel data techniques.....
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?
Usually we use the two terms interchangeably in our articles but whether is there any technical difference between them?
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.
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?
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?
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).
Thinking about food crop production this year, will there the surplus or shortage as a result of the global pandemic?
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?
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 ??
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
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?
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: email@example.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.
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;
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.
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.
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?
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.
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?
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.
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?
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.
How to explain the phenomenon of increase in price a commodity in the period of three generations, in a simple and layman’s language.
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.
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.
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?
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.
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?
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?
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?
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?
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.
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.
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.
we are trying to understand the relationship between industrial clusters and innovation in the context of indian manufacturing sector during the post reform period.
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.
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?
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?
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
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.
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.
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?
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.
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
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.
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)
a. Decision on salary accepting: taken (given by the firm)
b. Decision on quantity to buy: parameter of propensity to consume (exogenous)
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]
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
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.
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 ?
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 ?
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?
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.
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.