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Register a new userA Review of Disease and Development
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Ruiwu Liu
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Acemoglu and Johnson (2007) put forward the unprecedented view that health improvement has no significant effect on income growth. To arrive at this conclusion, they constructed predicted mortality as an instrumental variable based on the WHO international disease interventions to analyse this problem. I replicate the process of their research and eliminate some biases in their estimate. In addition, and more importantly, we argue that the construction of their instrumental variable contains a violation of the exclusion restriction of their instrumental variable. This negative correlation between health improvement and income growth still lacks an accurate causal explanation, according to which the instrumental variable they constructed increases reverse causality bias instead of eliminating it.
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Entrepreneurship is often touted for its ability to generate economic growth. Through the creative-destructive process, entrepreneurs are often able to innovate and outperform incumbent organizations, all of which is supposed to lead to higher employment and economic growth. Although some empirical evidence supports this logic, it has also been the subject of recent criticisms. Specifically, entrepreneurship does not lead to growth in developing countries; it only does in more developed countries with higher income levels. Using Global Entrepreneurship Monitor data for a panel of 83 countries from 2002 to 2014, we examine the contribution of entrepreneurship towards economic growth. Our evidence validates earlier studies findings but also exposes previously undiscovered findings. That is, we find that entrepreneurship encourages economic growth but not in developing countries. In addition, our evidence finds that the institutional environment of the country, as measured by GEM Entrepreneurial Framework Conditions, only contributes to economic growth in more developed countries but not in developing countries. These findings have important policy implications. Namely, our evidence contradicts policy proposals that suggest entrepreneurship and the adoption of pro-market institutions that support it to encourage economic growth in developing countries. Our evidence suggests these policy proposals will be unlikely to generate the economic growth desired.
This review paper identifies the core evidence of research on employee engagement , considering a stern challenge facing the financial sector nowadays. The study highlights the noteworthy knowledge gaps that will support human resource management practitioners to embed in the research towards sectoral context. Pertinent articles were selected through key search points and excerpt-related literature. The key search points covered the topic related to different terms of engagement for example employee engagement OR work engagement OR job engagement OR organization engagement OR staff engagement OR personnel engagement which were steered in diverse context particularly financial sector. Through critically reviewing the literature for the last 11 years i.e., 2009-2019, we discovered 91 empirical studies in financial sector. From these studies, we found the overall concept of engagement and its different determinants (e.g., organizational factors, individual factors, job factors) as well as its various outcomes (e.g., employee outcomes, organizational outcomes). We also formulated a conceptual model to expand the body of knowledge in the area of employee engagement for a better understanding of its predictors and outcomes. Besides, limitations of the study and future recommendations are also contemplated.
Understanding the microeconomic details of technological catch-up processes offers great potential for informing both innovation economics and development policy. We study the economic transition of the PR China from an agrarian country to a high-tech economy as one example for such a case. It is clear from past literature that rapidly rising productivity levels played a crucial role. However, the distribution of labor productivity in Chinese firms has not been comprehensively investigated and it remains an open question if this can be used to guide economic development. We analyze labor productivity and the dynamic change of labor productivity in firm-level data for the years 1998-2013 from the Chinese Industrial Enterprise Database. We demonstrate that both variables are conveniently modeled as Levy alpha-stable distributions, provide parameter estimates and analyze dynamic changes to this distribution. We find that the productivity gains were not due to super-star firms, but due to a systematic shift of the entire distribution with otherwise mostly unchanged characteristics. We also found an emerging right-skew in the distribution of labor productivity change. While there are significant differences between the 31 provinces and autonomous regions of the P.R. China, we also show that there are systematic relations between micro-level and province-level variables. We conclude with some implications of these findings for development policy.
We investigate structural change in the PR China during a period of particularly rapid growth 1998-2014. For this, we utilize sectoral data from the World Input-Output Database and firm-level data from the Chinese Industrial Enterprise Database. Starting with correlation laws known from the literature (Fabricants laws), we investigate which empirical regularities hold at the sectoral level and show that many of these correlations cannot be recovered at the firm level. For a more detailed analysis, we propose a multi-level framework, which is validated with empirically. For this, we perform a robust regression, since various input variables at the firm-level as well as the residuals of exploratory OLS regressions are found to be heavy-tailed. We conclude that Fabricants laws and other regularities are primarily characteristics of the sectoral level which rely on aspects like infrastructure, technology level, innovation capabilities, and the knowledge base of the relevant labor force. We illustrate our analysis by showing the development of some of the larger sectors in detail and offer some policy implications in the context of development economics, evolutionary economics, and industrial organization.
Economic shocks due to Covid-19 were exceptional in their severity, suddenness and heterogeneity across industries. To study the upstream and downstream propagation of these industry-specific demand and supply shocks, we build a dynamic input-output model inspired by previous work on the economic response to natural disasters. We argue that standard production functions, at least in their most parsimonious parametrizations, are not adequate to model input substitutability in the context of Covid-19 shocks. We use a survey of industry analysts to evaluate, for each industry, which inputs were absolutely necessary for production over a short time period. We calibrate our model on the UK economy and study the economic effects of the lockdown that was imposed at the end of March and gradually released in May. Looking back at predictions that we released in May, we show that the model predicted aggregate dynamics very well, and sectoral dynamics to a large extent. We discuss the relative extent to which the models dynamics and performance was due to the choice of the production function or the choice of an exogenous shock scenario. To further explore the behavior of the model, we use simpler scenarios with only demand or supply shocks, and find that popular metrics used to predict a priori the impact of shocks, such as output multipliers, are only mildly useful.
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