A new GLO Discussion Paper documents that entrepreneurship in advanced economies is in decline. It argues that negative scale effects from rising complexity, as well as long-run changes in aggregate demand due to inequality and rising energy costs, contribute to this.
The Global Labor Organization (GLO) is an independent, non-partisan and non-governmental organization that functions as an international network and virtual platform to stimulate global research, debate and collaboration.
Author Abstract: Entrepreneurship in advanced economies is in decline. This comes as a surprise: many scholars have anticipated an upsurge in entrepreneurship, and expected an “entrepreneurial economy” to replace the post-WW2 “managed” economy. Instead of the “entrepreneurial economy” what has come into being may perhaps better be labelled the “ossified economy.” This paper starts by document the decline. It then critically presents the current explanations offered in the literature. While having merit, these explanations are proximate and supply-side oriented. Given these shortcomings, this paper contributes a new perspective: it argues that negative scale effects from rising complexity, as well as long-run changes in aggregate demand due to inequality and rising energy costs, are also responsible. Implications for entrepreneurship scholarship are drawn.
A new GLO Discussion Paper tests the performance of cross-survey imputation methods to estimate poverty for a sample of refugees in Chad.
The Global Labor Organization (GLO) is an independent, non-partisan and non-governmental organization that functions as an international network and virtual platform to stimulate global research, debate and collaboration.
Author Abstract: Household consumption surveys do not typically cover refugee populations, and poverty estimates for refugees are rare. This paper tests the performance of cross-survey imputation methods to estimate poverty for a sample of refugees in Chad, by combining United Nations High Commissioner for Refugees survey and administrative data. The proposed method offers poverty estimates based on administrative data that fall within a 95 percent margin of poverty estimates based on survey consumption data. This result is robust to different poverty lines, sets of regressors, and modeling assumptions of the error term. The method outperforms common targeting methods, such as proxy means tests and the targeting method currently used by humanitarian organizations in Chad.
A new GLO Discussion Paper replicates two published articles by seven independent research teams each to document the huge variety of different research strategies chosen and their large differences in outcomes.
The Global Labor Organization (GLO) is an independent, non-partisan and non-governmental organization that functions as an international network and virtual platform to stimulate global research, debate and collaboration.
Author Abstract: Researchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many-analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size. Statistical significance varied across replications, and for one of the studies the effect’s sign varied as well. The standard deviation of estimates across replications was 3-4 times the typical reported standard error.
Like in the financial market crisis, the world struggles again in the #coronavirus crisiswith data needs to proper respond to the challenges. Why are data so important, and why are social media data not a simple solution? Some insights from an interview with data scientist Pablo de Pedraza.
Some core messages of the interview:
Data is a source of economic growth and innovation. The data flow in a data economyis semicircular – from households and firms to data holders, but not back.
If knowledge extraction from data is a natural monopoly, the amount of knowledge generated is below the socially desirable amount.
Many agents that could generate valuable knowledge do not have enough access to data.
The more citizens are responding to Covid-19 apps, the more data and knowledge we have about the virus.
In a data economy, the race for innovation is a race for data.
A related new research paper of Pablo de Pedraza on the topic is:
The first use of social media data for policy analysis in response to data needs in a huge crisis has been made in the context of the 2009 financial market crisis:
GLO FellowPablo de Pedraza (European Commission, DG Joint Research Centre) is an Economist interested in the use of web data for economic research. His research interests are web data, life satisfaction and the semicircular flow of the data economy. The scientific output expressed does not imply a European Commission policy position. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication.
Middle photo by Mika Baumeister on Unsplash
Interview
GLO:What is the “data economy” and its “semicircular flow”?
Pablo de Pedraza: The “Data economy” is an economy where data plays a crucial role. From a consumption perspective, personal data is similar to money; citizens pay online services with their data. From a production point of view, data is like oil; a raw material to produce digital services. Data is a source of economic growth and innovation. Theoretical economic concepts also apply to the “data economy” which has its own market failures. The “semicircular” flow is a theoretical model that aims to simplify the complex reality of the “data economy.” It facilitates discussion about the why and how of data policy. The general idea is that the data flow is semicircular; from households and firms to data holders, but not in the other direction. Households and firms receive data-driven services that are the result of knowledge extracted from data. If citizens would receive data, they would not have the capacity to process nor extract knowledge from that data. One of the objectives of data policy is to empower the individual.
GLO:Why is the level of knowledge below the socially desirable amount?
Pablo de Pedraza: The question is whether the process of extracting knowledge from data is a natural monopoly, which is an empirical question for which we have no answer yet. We can observe how data holders like large technology companies behave. They are data hungry, in the search for the perfect marketing tool. In econometric terms, they are in a race towards N=All and X=everything. If knowledge extraction from data is a natural monopoly, and data holders are profit maximization agents and monopoly theory holds, the amount of knowledge generated is below the socially desirable amount. Therefore, public intervention should focus on increasing knowledge generation. What kind of knowledge? Data is a different type of good depending on the kind of knowledge generated. Using data to generate market power is a demerit good. Data is a merit good if used: to deliver nimbler public policy, to protect competitive markets, to forecast economic cycles, to protect consumer’s rights, and study a pandemic.
GLO:Some people say, we have enough data, but not the right one….
Pablo de Pedraza: The data economy has its own sources of access inequalities similar to income inequalities. Many agents that could generate merit knowledge, such as the scientific community, central banks or anti-trust authorities, do not have enough access to data. For example, research literature shows how online searches can improve forecasting models. One of the main conclusions from that literature is that better understanding of results needs the disclosure of more data. More accurate forecasting is an example of merit knowledge that benefits the whole society, including data holders.
GLO:Can your theory help us to understand the data challenge in the coronavirus crisis?
Pablo de Pedraza: Yes. Think about mobile apps to track Covid-19. The more citizens responding to Covid-19 apps, the more data and knowledge we have about the virus. The semicircular flow of the economy defines the data sharing Laffer curve. It explains the theoretical determinants of optimum data sharing as the point where society generates the maximum amount of data and merit knowledge. Principles that define the curve, such as trust, apply to the covid-19 data challenge. When citizens understand the data dimension of the economy and trust the rule of law, they are more willing to contribute to a solution, install the app, and give consent to share their data. If they do not understand what they are giving their consent for, they will be hesitant to install the app and therefore; data generated will be lower and knowledge will be below the socially desirable amount.
GLO: What are the conclusions for data sharing policies?
Pablo de Pedraza: In a data economy, the race for innovation is the race for data. Leaving data policy only in the hands of data holders will not solve antitrust concerns. The lack of competition stifles innovation although it may initially attract investment. However, excessive intervention discourages investment from data holders and generate surveillance concerns. Countries able to empower well-informed citizens by developing their data literacy, fostering user centric approaches, building strong public data infrastructures and institutions will win the race. Citizens operating in a secure environment will generate more data and increase innovation. In my opinion, data sharing policies are just as vital and important as fiscal and monetary policies. The semicircular flow of the economy is a data sharing theoretical framework. The data dimension of the covid-19 crisis is an illustrative example of that framework.
************* With Pablo de Pedraza spoke Klaus F. Zimmermann, GLO President. Further activities and reports of the GLO Research Cluster on the coronavirus.
The Institute for Economic and Social Research (IESR) at Jinan University and the Global Labor Organization (GLO) intensify their collaborations, as IESR DirectorShuaizhang Feng and GLO President Klaus F. Zimmermann have declared.
IESR Director Shuaizhang Feng has been appointed GLO Country Lead China. IESR provides institutional support as a GLO-related institution and serves as a local host for GLO activities.
Third IESR-GLO Joint Conference.IESR and GLO are jointly organizing a virtual conference on the economic issues of Covid-19. The event is a platform for economists to exchange ideas on improving responses to Covid-19 through a series of presentations of high-quality academic papers. Keynote addresses by Daron Acemoglu (MIT) and Charles Manski (Northwestern University). The Virtual Conference takes place on June 5-7, 2020. Deadline for paper submission is May 24. MORE INFO.
Journal of Population Economics: Klaus F. Zimmermann is Editor-in-Chief; Shuaizhang Feng one of the Editors.
IESR-GLO Conferences 2018 – 2020.
2020 June 5-7: Guangzhou, Jinan University, China.Third IESR-GLO Joint Conference on “The Economics of Covit-19”. Virtual event. MORE INFO.
2019, March 21-22: Guangzhou, China. Jinan University.IESR-GLO Conference on “Belt and Road” Labor Markets. Organizers: Shuaizhang Feng and Klaus F. Zimmermann. A focus was China, South Asia and South East Asia. GLO News Report. IESR Report LINK WEBSITE.
2018, March 11-20: Guangzhou/China; Jinan University; Research and contact visit of the GLO President. Career seminar provided by the GLO President. First GLO-IESR Conference on “Labor Economics” and various paper presentations by GLO Fellows. Public Policy Lecture of the GLO President on European Migration. Debate with Editor of “Social Science in China” by the GLO President and Editor-in-Chief of the Journal of Population Economics. Debate with Dean & GLO Fellow Shuaizhang Feng by the GLO President on unemployment.
A new GLO Discussion Paper contains robust evidence that retirement causally improves overall life satisfaction.
The Global Labor Organization (GLO) is an independent, non-partisan and non-governmental organization that functions as an international network and virtual platform to stimulate global research, debate and collaboration.
Author Abstract: This paper presents robust evidence that retirement causally improves overall life satisfaction which is subsequently explained by improvements in satisfaction with one’s financial situation, free time, health, and participation in local community activities. Furthermore, while the positive wellbeing impact of retirement is sizable initially, it fades after the first 3 years. We find that the improvements in financial satisfaction upon retirement are only observed for low-income individuals. However, the wellbeing impact of retirement does not differ by gender, educational, occupational, economic or marital backgrounds. We also explore several potential explanations for our findings. This paper employs a fixed effect instrumental variable model, which exploits the discontinuity in the eligibility ages for state pension to construct an instrument for retirement, and 18 waves of high-quality Australian panel data. The results also suggest that failing to adequately account for the endogeneity of retirement would result in a downward-biased estimate of a positive wellbeing impact of retirement.
A new paper published in the Journal of Population Economics finds that information and communications technology (ICT) significantly increases students’ likelihood of obtaining a job offer in the labor market and higher wages. The positive effect comes from students’ increased use of computers and the internet for job search.
Journal of Population Economics (2020) 33, Issue 3: 1101-1126 FREE READ LINK
Author Abstract: This paper presents some of the first evidence on the effect of information and communications technology (ICT) on college students’ labor market performance. Using a large, representative survey of college students in China, we examine outcomes before and after students were exposed to technology-aided instruction, compared with students who were not exposed to such instruction. The results indicate that the ICT program significantly increased students’ likelihood of obtaining a job offer in the labor market and the wage they were offered. The positive effect comes from students’ increased use of computers and the internet for job search. While most previous studies of the use of technology in education focus only on students’ academic achievement and find zero or negative effects, our study demonstrates that technology may be an effective tool for improving college students’ labor market performance, and that the potential benefits of technology might be underestimated if we focus only on test scores and ignore students’ career development.
LEAD ARTICLE OF ISSUE 3: Blau, F.D., Kahn, L.M., Brummund, P. et al., Is there still son preference in the United States?. Journal of Population Economics33, 709–750 (2020). READ LINK FREE. https://doi.org/10.1007/s00148-019-00760-7
A new GLO Discussion Paperuncovers patterns of transition into and out of different classes of the consumption distribution in India over a quarter century.
The Global Labor Organization (GLO) is an independent, non-partisan and non-governmental organization that functions as an international network and virtual platform to stimulate global research, debate and collaboration.
Author Abstract: We analyze the Indian National Sample Survey data spanning 1987/88–2011/12 to uncover patterns of transition into and out of different classes of the consumption distribution. At the aggregate level, income growth has accelerated, accompanied by accelerating poverty decline. Underlying these trends is a process of mobility, with 40–60 percent of the population transitioning between consumption classes and increasing mobility over time. Yet, the majority of those who escape poverty remain vulnerable. Most of those who are poor were also poor in the preceding period and, thus, are likely to be chronically poor. The characteristics of upwardly mobile households contrast with those of the poor; these households are also far less likely to experience downward mobility. We also find that states exhibit heterogenous mobility patterns.
A new paper published in the Journal of Population Economics provides a model that can account for the possibly negative correlation between population growth and productivity growth.
Journal of Population Economics (2020) 33, Issue 3: 1025-1068 FREE READ LINK
GLO Fellow Klaus Prettner
Author Abstract: To reconcile the predictions of research and development (R&D)-based growth theory regarding the impact of population growth on productivity growth with the available empirical evidence, we propose a tractable, continuous-time, multisector, R&D-based growth model with endogenous education and endogenous fertility. As long as the human capital dilution effect is sufficiently weak, faster population growth may lead to faster aggregate human capital accumulation, to faster technological progress, and, thus, to a higher growth rate of productivity. By contrast, when the human capital dilution effect becomes sufficiently strong, faster population growth slows down aggregate human capital accumulation, dampens the rate of technical change, and, thus, reduces productivity growth. Therefore, the model can account for the possibly negative correlation between population growth and productivity growth in R&D-based growth models depending on the strength of the human capital dilution effect.
LEAD ARTICLE OF ISSUE 3: Blau, F.D., Kahn, L.M., Brummund, P. et al., Is there still son preference in the United States?. Journal of Population Economics33, 709–750 (2020). READ LINK FREE. https://doi.org/10.1007/s00148-019-00760-7
A new GLO Discussion Paperinvestigates Covid-19 infection detection by using a machine learning procedure for hardly reliable data to identify structural breaks. It finds successfully forItaly three structural breaks that can be related to the three different national level restrictive measures: the school closure, the main lockdown and the shutdown of non-essential economic activities.
The Global Labor Organization (GLO) is an independent, non-partisan and non-governmental organization that functions as an international network and virtual platform to stimulate global research, debate and collaboration.
Author Abstract: Feedback control-based mitigation strategies for COVID-19 are threatened by the time span occurring before an infection is detected in official data. Such a delay also depends on behavioral, technological and procedural issues other than the incubation period. We provide a machine learning procedure to identify structural breaks in detected positive cases dynamics using territorial level panel data. In our case study, Italy, three structural breaks are found and they can be related to the three different national level restrictive measures: the school closure, the main lockdown and the shutdown of non-essential economic activities. This allows assessing the detection delays and their relevant variability among the different measures adopted and the relative effectiveness of each of them. Accordingly we draw some policy suggestions to support feedback control based mitigation policies as to decrease their risk of failure, including the further role that wide swap campaigns may play in reducing the detection delay. Finally, by exploiting the huge heterogeneity among Italian provinces features, we stress some drawbacks of the restrictive measures specific features and of their sequence of adoption, among which, the side effects of the main lockdown on social and economic inequalities.
The Journal of Population Economics welcomes submissions dealing with the demographic aspects of the Coronavirus Crisis.After fast refereeing, successful papers are published in the next available issue. An example:
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