The power of positivity? The influence of positive psychological capital language on crowdfunding performance

We extend the entrepreneurship literature to include positive psychological capital — an individual or organization's level of psychological resources consisting of hope, optimism, resilience, and confidence — as a salient signal in crowdfunding. We draw from the costless signaling literature to argue that positive psychological capital language usage enhances crowdfunding performance. We examine 1726 crowdfunding campaigns from Kickstarter, finding that entrepreneurs conveying positive psychological capital experience superior fundraising performance. Human capital moderates this relationship while social capital does not, suggesting that costly signals may, at times, enhance the influence of costless signals. Post hoc analyses suggest findings generalize across crowdfunding types, but not to IPOs.     

Inequality and entrepreneurial thresholds

We explore the relationship between inequality and entrepreneurial activity. Drawing on cross-sectional data from a largescale survey of the economic conditions of individuals across India, we develop a number of dimensions of inequality to explore empirically how inequality interacts with entrepreneurship, operationalized as self-employment or as employing other people. We find compelling evidence that there are thresholds to becoming self-employed, and even more so to assembling the combinations of resources and personal attributes required to become an employer. Greater inequality leaves more people unable to make the transition to self-employment, leaving casual laboring as the occupation of necessity. At the same time, inequality increases the number of employers in a society, by concentrating resources - particularly land and finance - enough for significant numbers of people to be able to cross this higher threshold. Lastly, greater differentiation into social or religious groups curtails the ability to cross either entrepreneurial threshold, presumably by limiting the extent and benefits of social networks of value for entrepreneurship.     

Measuring Inflation Anchoring and Uncertainty: A U.S. and Euro Area Comparison

We use several U.S. and euro‐area surveys of professional forecasters to estimate a dynamic factor model of inflation featuring time‐varying uncertainty. We obtain survey‐consistent distributions of future inflation at any horizon, both in the U.S. and the euro area. Equipped with this model, we propose a novel measure of the anchoring of inflation expectations that accounts for inflation uncertainty. Our results suggest that following the Great Recession, inflation anchoring improved in the United States, while mild de‐anchoring occurred in the euro area. As of our sample end, both areas appear to be almost equally anchored.     

Social capital and well-being in the Italian provinces

Recent years witnessed a growing interest in the concept of well-being and quality of life, as alternative to the Gross Domestic Product (GDP). The determinants of well-being, especially at the regional and provincial levels, is understudied in a macro perspective, as opposed to a micro perspective (individuals, survey data) that has been the dominant approach until recently. In this paper, we estimate an empirical model for the Italian NUTS-3 provinces to evaluate the role of social capital on well-being by using aggregated (provincial) data. Our findings suggest that social capital, social security programs, income, and grant-making activities by Bank Foundations, even though not uniformly distributed across Italy, positively affect well-being, thus contributing to explain the persistent dualism that characterizes the Italian economy.     

Personal Income Tax Reform in China in 2018 and Its Impact on Income Distribution

In the context of personal income tax (PIT) reform in China in 2018, this paper examines some of the major issues of concern regarding the reform and income distribution. Using the China Personal Income Tax Micro‐simulation model, the paper compares the differences between the 2011 and 2018 PIT systems, and finds that residents relying on different income sources may face a large degree of real tax rate change. Once the tax system is altered to PIT 2018, the coverage of PIT for wage earners will decrease from 46.9 to 23.4 percent, the income redistributive effect will drop from 1.95 to 1.22 percent and the PIT's role in fiscal revenue will also be negatively affected. Nevertheless, if individual income continues to grow, the share of PIT in fiscal revenue is expected to return to the 2018 level in 2022, but its income redistribution function is difficult to recover in the short term. The paper finds that the effect of PIT on income distribution depends on the tax structure. Gradual transition to an “entirely comprehensive” tax system when conditions are appropriate will achieve better income redistribution results at a lower average tax rate.     

Sources of Productivity Growth Dynamics: Is Japan Suffering From Baumol's Growth Disease?

This study examines the sources of labor productivity growth dynamics in Japan (1970–2010) and investigates the extent to which Japanese economic performance has been affected by Baumol's growth disease (BGD). We find that BGD silently undermines Japanese economic growth. However, the magnitude is miniscule, and consequently the aggregate labor productivity growth rate has not been decreasing monotonically. We also explore how BGD is arising and why it is small in the Japanese economy. BGD is weak because (1) the positive Baumol growth effect is also working in certain services sectors and (2) BGD is not a durable phenomenon: even if a sector begins to suffer from BGD, it is likely to recover quickly.     

Impact of modern communication infrastructure on productivity,production structure and factor demands of US industries: Impact revisited

This study investigates the contribution of modern communication infrastructure characterized by high speed broadband access network on the productivity growth, production structure and factor demands for US industries and for the aggregate economy. To evaluate such contribution, we modify the traditional cost function by incorporating communication infrastructure as input in production process in conjunction with other public infrastructures. The network externality and spillover effect of broadband access technology are captured by introducing broadband penetration rate as a shift factor in industry level production function. Empirical results show that the increased use of modern communications infrastructure increases the productivity of all industries with wide variations across industries. Estimated impacts on input demands show that increase in use of communications infrastructure service saves labor and materials and increase the demand for private capital. Finally, aggregate social rate of return on such investment has been estimated for policy implications.     

Does corruption slow down innovation? Evidence from a cointegrated panel of U.S. states

I investigate the long-run relationship between corruption and innovative activity using annual data from 48 contiguous U.S. states between 1977 and 2006. Using U.S. data allows me to work with a panel long enough to exploit time series properties of the data. I use two different measures of innovative activity: one measuring the quantity and the other measuring the quality of the patents granted. I also use two different measures of corruption: one based on the number of corruption convictions, the other based on number of corruption stories covered in Associated Press news wires. Following Pedroni (1999, 2000), I estimate the cointegrating relationship between corruption and innovative activity with Fully Modified Ordinary Least Squares (FMOLS). The results indicate that corruption indeed slows down innovation in the long-run.     

Increasing linkages among European regions. The role of sectoral composition

This paper analyses changes in economic regional interlinkages in Europe over time and investigates the factors that could explain the dynamics of these changes. Our four main findings are the following: (i) we detect a significant surge in regional synchronisation after the Great Recession; (ii) we identify the regions most interrelated with the rest of Europe, namely, Ile de France, Inner London and Lombardia; (iii) we find that sectoral composition explains regional synchronisation in Europe, mainly after the Great Recession and (iv) we document that sectoral composition has important implications for aggregate economic fluctuations, in particular, that similarities in services-related sectors across regions explain a nonlinear relationship between sectoral composition and regional business cycle synchronisation. We also propose a new method to measure time-varying synchronisation in small samples that combines regime-switching models and dynamic model averaging.     

Terror per Capita

Studies on the correlates of terrorism usually analyze total numbers of attacks or victims per country. However, what we may ultimately care about in terms of policy recommendations is the likelihood of any individual being subject to the respective phenomenon. Thus, we propose and explore a simple alternative measure of terrorism: terror per capita. Studying terror per capita across 162 countries from 1970–2015, the associated correlates differ substantially in terms of sign, levels of statistical significance, and magnitude from those when analyzing total terror. We illustrate two cases in point, serving as proof of concept. First, democracy, often associated with more total terror, emerges as a marginally negative predictor of terror per capita. Second, a larger share of Muslims in society is associated with a positive and statistically significant link to total terror, but emerges as a negative predictor of terror per capita. We find similar changes in sign and statistical relevance for GDP per capita and language fractionalization as correlates of terrorism. Depending on the policy question, studying terror per capita can greatly enhance our understanding of terrorism drivers, especially when analyzing data across countries with vastly differing population sizes.