Applied Economics - Science topic

Call for papers: 2025 2nd International Conference on Applied Economics, Management Science and Social Development (AEMSS 2025) will be held in Kunming, China during March 28-30, 2025.

大会官网(投稿网址）：https://ais.cn/u/Yz2auy

大会时间：2025年02月28-30日

大会地点：中国-昆明

提交检索：CPCI,CNKI

第二届应用经济学、管理科学与社会发展国际学术会议（AEMSS 2025）将于2025年3月28-30日在中国昆明举行。会议主要围绕应用经济学、管理科学、社会发展等研究领域展开，旨在为从事经济、管理等相关研究的专家学者提供一个交流科研成果和前沿技术的平台，了解学术发展趋势，拓宽研究思路，加强学术研究和讨论，促进学术成果产业化合作。

经济增长与技术创新

管理创新与经济

互联网背景下的经济

经济管理

世界经济

数字经济

区域经济...

大数据背景下的管理

互联网背景下的管理

管理信息系统

企业管理

政府管理

国有企业管理

国际化经营管理

商业管理

战略管理

营销管理...

社会发展理论研究

思想政治教育

构建和谐社会

全面发展与对策研究

新时代理论与思想

社会变迁与生态文明

社会治理创新

社会工作基础...

所有的投稿都必须经过2-3位组委会专家审稿，经过严格的审稿之后，录用的论文将发表到Atlantis Press 出版社旗下proceeding系列《Advances in Economics, Business and Management Research》(Online ISSN: 2352-5428)，且将提交至CPCI (Web of Science) 和CNKI检索。

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The article "How to Write Applied Papers in Economics" by Marc F. Bellemare provides a comprehensive guide for graduate students and researchers on the process of writing applied economics papers. Bellemare's article is structured to eliminate the guesswork involved in writing applied economics papers. It serves as a draft chapter from a forthcoming book and aims to provide clear, actionable advice for new graduate students and seasoned researchers alike. Key Components of an Applied Economics Paper The article meticulously breaks down the various components of an applied economics paper, discussing each in detail and in the order they are typically tackled during a research project. These components include: 1. Introduction: Bellemare emphasizes the importance of a strong introduction that clearly states the research question, its significance, and the contribution of the paper to the existing literature. 2. Literature Review: The literature review should not only summarize relevant previous work but also critically evaluate it to highlight gaps that the current research aims to fill. 3. Data and Methodology: This section should provide a detailed description of the data sources, the empirical strategy, and the methods used to analyze the data. Bellemare stresses the need for transparency and reproducibility in this part of the paper. 4. Results: The results section should present the findings in a clear and logical manner, using tables and figures where appropriate. Bellemare advises against overloading this section with too many robustness checks, suggesting that the main results should be the focus. 5. Discussion and Conclusion: This section should interpret the results, discuss their implications, and suggest areas for future research. Bellemare highlights the importance of linking the findings back to the research question and the broader literature. Practical Advice Bellemare offers several practical tips throughout the article: • Clarity and Precision: He advises writers to be clear and precise in their language, avoiding jargon and overly complex sentences. • Consistency: Consistency in terminology and formatting is crucial for readability and professionalism. • Engagement: Bellemare encourages writers to engage the reader by telling a compelling story with their research, making the paper interesting and accessible. Overall, "How to Write Applied Papers in Economics" is an invaluable resource for anyone involved in writing or teaching applied economics. Bellemare's detailed breakdown of the paper-writing process, combined with his practical advice, makes this article a must-read for graduate students and researchers aiming to publish their work in peer-reviewed journals. #write #appliedpapers #writing #WritingResources #AcademicTools #ResearchTools #WritingTools #AcademicSkills #ResearchSkills #WritingSkills #AcademicGrowth #ResearchGrowth #Writin

Jeffrey H. Dorfman, Scott H. Irwin, and David Zilberman's article "The Future of Agricultural and Applied Economics Departments," published in Applied Economic Perspectives and Policy, explores the evolving role of Agricultural and Applied Economics (AAE) departments in the United States. Summary The article examines how AAE departments have adapted to serve traditional and new stakeholders under the land grant mission, which includes extension, research, and teaching. It discusses the strategic direction of these departments in response to changing demands and the need to solve current and future economic problems related to the food supply chain and bioeconomy. Key Findings 1. Mission and Evolution: AAE departments have historically focused on agricultural issues but are now expanding to address broader economic problems. This evolution is driven by the need to remain relevant and provide value to society. 2. Interdisciplinary Collaboration: The authors emphasize the importance of interdisciplinary collaboration, particularly with the physical sciences, to tackle complex economic issues. This approach can enhance the impact and relevance of AAE research. 3. Strategic Direction: The article highlights the need for AAE departments to strategically align their focus with stakeholder demands. This includes balancing traditional agricultural economics with emerging areas such as the bio-economy. Implications The findings suggest that AAE departments must continuously adapt to changing economic landscapes and stakeholder needs. By embracing interdisciplinary collaboration and focusing on relevant economic problems, these departments can enhance their contributions to society and improve their academic standing. Conclusion "The Future of Agricultural and Applied Economics Departments" provides valuable insights into the strategic evolution of AAE departments. It underscores the importance of adapting to new challenges and opportunities to maintain relevance and impact in the field of economics. #Research #Writing #WorkLifeBalance #AcademicLife #PhDLife #GradSchool #Thesis #Dissertation #AcademicWriting #TimeManagement

Does the use of theory or theories mandatory in social science research including economics and business administration areas?

I am doing different researches to continue the empirical analysis I started with my Applied Economics paper about real depreciation of the euro and the change of European countries’ trade balances .

I am not sure that the empirical methodology I am using, i.e. an ARDL methodology, based on the ECM, proposed by Engle and Granger (1987), that gives both short-run and long-run results simultaneously, may be modified.

The main doubts I have are the following ones:

1) What about other drivers besides the macroeconomic variables in question? I am sure political uncertainty might play a role.

2) Many of the diagnostic tests (such as the LM test) show issues in the model (such as autocorrelation in the residuals). How have these tests informed the model? has it been respecified to correct any issues? I have noticed that many previous "J-Curve" papers tend to present, and immediately ignore, these diagnostic tests. Anywat the future research should not make the same mistake!

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Would workers desire labor unions less if Maslow’s Hierarchy of Needs guided distributing an economic basis for each individual? How? Why?

Does status mean mimetic influence over evolutionary competition?

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?

How do I monetize my ResearchGate account?

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?

I have a dataset with T=11(2010-2020) and N=63(provinces). I want to estimate the causality relationship in short run and long run between 2 variables. Which model can be suitable?

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My submission's status of "within Editor" have been two weeks and it does not change. So anyone know the reviewing process for the journal of Applied Economics Letters.

Lets begin with understanding money as liquid, which is how CHINESE describes MONEY as WATER.

The expression "money is like water" is often attributed to Chinese culture, and it reflects a particular mindset about wealth and its fluid nature. While not everyone in China may use this expression, it does capture a common attitude towards money. Here are some reasons why money is sometimes metaphorically equated with water in Chinese culture:

If we conceptualize CO2 as liquidity rather than a gas or vapor, we are essentially considering carbon dioxide as a form of tradable liquid asset that represents environmental impact. This approach adds an additional layer to the integration of CO2 into a financial system. Here's how this could be incorporated into the concept:

This conceptualization aims to integrate the idea of liquidity into the carbon economy, treating CO2 as a tradable liquid asset with a value that can be influenced by market forces. It introduces the dynamics of supply, demand, and liquidity management into the broader context of environmental sustainability. As with any innovative financial system, careful planning, regulation, and adaptation are crucial for its successful implementation. Additionally, it's essential to consider potential unintended consequences and continually assess the system's effectiveness in achieving environmental goals.

Here's a conceptual approach to a real-world system where money is pegged to CO2 supply and demand:

It's important to note that while this concept provides a real-world approach, it is highly complex and would face numerous challenges, including international cooperation, regulatory frameworks, and the need for a robust infrastructure to manage the carbon credit system.

Pegging an international currency to a conception of CO2 reduction involves linking the value of the currency to the success and progress of global efforts in reducing carbon emissions. Here's a conceptual framework for how this might be achieved:

Implementing such a system would require significant coordination, cooperation, and commitment from the international community. It would also involve addressing challenges such as varying levels of economic development, differing national priorities, and potential resistance to adopting a new international currency system. Additionally, technological advancements in monitoring and verification of carbon reduction efforts would play a crucial role in the success of this conceptual framework.

Pegging CO2 as liquidities to currency exchanges could potentially introduce innovative financial mechanisms to overcome hurdles in CO2 reduction efforts. Here are ways in which this approach might help address challenges:

How it Helps: By pegging CO2 as liquidities to currency exchanges, you create a market for trading carbon assets. This introduces market-driven incentives for businesses and nations to reduce emissions, as they can profit from selling excess carbon liquidities or face costs for exceeding their allocated limits.

How it Helps: Liquid markets are often more flexible. This flexibility can be harnessed to adapt to varying circumstances, allowing entities to buy or sell carbon liquidities based on changing economic conditions or technological advancements. It provides a dynamic system that can adjust to evolving emission reduction challenges.

How it Helps: A liquid carbon market could facilitate global collaboration. Countries with a surplus of carbon liquidities can trade with those facing challenges, promoting a more efficient allocation of resources for emissions reduction. This approach encourages a collaborative, international effort to achieve overall reduction targets.

How it Helps: The concept of CO2 liquidities as a tradable asset could attract investments in sustainable and low-carbon projects. Financial instruments backed by carbon liquidities, such as bonds or green funds, may become attractive to investors, funneling capital into initiatives that contribute to emission reduction.

How it Helps: Liquid markets often operate with a high degree of transparency. This transparency could help overcome challenges related to verification and trust. It ensures that the buying and selling of carbon liquidities are conducted with integrity, minimizing the risk of fraudulent activities.

How it Helps: Establishing reserves of carbon liquidities can act as a stabilizing mechanism. During economic downturns or unexpected challenges, entities can tap into these reserves to meet emission reduction targets without facing excessive financial burdens, promoting long-term stability in carbon markets.

Economic Growth with Emission Reduction:How it Helps: Liquid carbon markets could provide a mechanism for balancing economic growth with emission reduction. As economies grow, they may need additional carbon liquidities, which can be acquired through the market. This allows for economic development while ensuring adherence to overall carbon reduction goals.

How it Helps: Liquid carbon markets could attract greater participation from the private sector. Businesses can actively engage in emissions reduction efforts by buying and selling carbon liquidities, aligning their financial interests with environmental goals and contributing to a more sustainable economy.

How it Helps: The creation of financial instruments backed by carbon liquidities, such as carbon futures or options, could provide businesses and investors with tools to manage and mitigate risks associated with emissions. This can enhance financial planning and encourage long-term sustainability.

How it Helps: A liquid carbon market could be designed to include public participation, allowing individuals to buy and sell carbon liquidities. This engagement can increase public awareness and encourage environmentally conscious behavior, as individuals see a direct link between their actions and the carbon market.

While pegging CO2 as liquidities to currency exchanges introduces potential benefits, it's crucial to recognize that implementing such a system would still require careful design, international cooperation, and ongoing monitoring to ensure its effectiveness in promoting meaningful CO2 reduction. Additionally, considerations for potential market manipulation, regulatory frameworks, and social equity issues should be addressed in the development and implementation of this approach.

A political economist would likely analyze the concept of pegging CO2 to currency exchanges from a multidimensional perspective, considering the economic, political, and social implications of such an approach. Here are some aspects a political economist might consider:

Analysis: A political economist would assess whether pegging CO2 to currency exchanges promotes economic efficiency by creating market-driven incentives for emissions reduction. They might evaluate the efficiency of the proposed carbon market in allocating resources and encouraging innovation in low-carbon technologies.

Analysis: Political economists would scrutinize the distributional effects of the proposed system. They might investigate how the costs and benefits are distributed among different socioeconomic groups, regions, and nations. Consideration would be given to whether the approach exacerbates or mitigates existing inequalities.

Analysis: Political economists would study the feasibility of achieving international cooperation through a liquid carbon market. They might analyze the political dynamics and power structures among nations, assessing whether the proposed system provides sufficient incentives for countries to collaborate on emission reduction efforts.

Analysis: Political economists would examine the choice of policy instruments within the proposed framework. They might consider the use of market-based mechanisms, regulatory approaches, and the role of government intervention. The analysis would explore how different policy instruments align with political and economic ideologies.

Analysis: Political economists would assess the political will required to implement and sustain such a system. They might analyze potential political resistance, lobbying efforts, and the ability of governments to commit to long-term emission reduction targets, considering the political economy of climate change policies.

Analysis: Political economists would scrutinize the environmental justice implications of the proposed approach. They might assess whether the system disproportionately affects vulnerable communities or if it addresses historical disparities in environmental burdens.

Analysis: Political economists would consider the role of the private sector within the proposed framework. They might analyze how corporations influence policy decisions, whether the approach aligns with corporate interests, and how the involvement of the private sector may impact the effectiveness of emission reduction efforts.

Analysis: Political economists would evaluate the stability of the proposed system over the long term. They might consider the potential for policy reversals with changes in government or economic conditions, assessing the resilience of the system to political volatility.

Analysis: Political economists would examine the global governance structures and institutions needed to support the proposed system. They might explore the role of international organizations, the effectiveness of existing institutions, and the need for new forms of global governance in managing a liquid carbon market.

Analysis: Political economists would consider how the public perceives the proposed approach and whether it aligns with democratic principles. They might assess the level of public engagement, participation, and the legitimacy of decision-making processes in shaping climate policies.

In essence, a political economist would analyze the proposed approach within the broader context of political and economic systems, considering its implications for power dynamics, social equity, and the overall political economy of climate change mitigation. This multidimensional analysis would provide insights into the feasibility, effectiveness, and potential challenges associated with pegging CO2 to currency exchanges.

Image Source: https://www.investopedia.com/terms/c/currency-peg.asp

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?

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 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,

The following articles are related to the above issue in some respects:

FAMILY 500 PLUS PROGRAMS AND FLAT PLUS WITH KEY INSTRUMENTS FOR PRIVATE SOCIAL POLICY IN POLAND

NATIONAL HOUSING PROGRAM OF THE MAIN STRATEGIC AND PROGRAM DOCUMENT FOR THE CURRENT STATE RESIDENTIAL POLICY OF THE STATE

THE IMPORTANCE OF INTRODUCING THE FAMILY 500 PLUS PROGRAMME AS A KEY FACTOR IN COMPREHENSIVE FAMILY INVESTMENT POLICY IN POLAND

Current and future objectives of pro-family social policy based on the Family 500 Plus programme

The material and economic situation of households in Poland and the importance of introducing the Family 500 Plus programme as part of a comprehensive pro-family social policy

I invite you to collaborate with me on research projects.

Best wishes,

Dariusz Prokopowicz

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.

Thank you.

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,

Santiago.

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

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.

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

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

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.

Best

Ibrahim

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?

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?

For example, I would like to change current to constant prices (2003).

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 ??

Does adding renewable energy sources to smart grid change the price?

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?

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

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.

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 have tested the unit root for my panel data, some of the variables are stationary in first difference, and some of them in level, should I take any log for my variables? But the dependent variable is stationary at first difference.

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.

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?

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?

Causality

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.

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.

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).

Under what circumstances can GMM be used and what problems of panel regression does it address.

Hello Everyone! Could any one recommend me better time series model for forecasting gross agricultural production growth with less statistical noise?

hi, can i use GMM in unbalanced panel data with N=35 and T=36 ? thank you

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. 

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

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?

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?

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!

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?

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.

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.

In the context of India.I need a variable with quarterly frequency.

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?

Kindly share materials that will help me understand how to interpret the output of "DASP: Stata modules for distributive analysis".

Thank you.

economics development international trade panel data 

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.

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.