Research in Economics最新文献

This paper investigates the link between close banking relationships and European manufacturing firms’ defaults. Based on binary outcomes (i.e., Logit, Probit, Complementary log-log) and discrete-time models, the empirical analysis reveals that enduring lending relationships present benefits in reducing firms’ temporary and permanent defaults. This evidence suggests that, in a framework of limited credit access that may compromise firms’ survival, relationship lending might represent an effective tool for overcoming asymmetric information problems, helping firms relax credit constraints, encouraging greater discipline in their managers, and preventing failure.

Comparison among Cournot, Bertrand and monopolistic competition receives recent attention in industrial organization, but not in New Economic Geography. To fulfill this gap, we examine how the difference in market structures affects industry location in a footloose capital model. We find that the home market effect is strongest in Cournot competition, second strongest in Bertrand competition, and weakest in monopolistic competition. And, we link the insights in industrial organization with our model of geography.

Migration has increased in many parts of the world for a variety of reasons. In our study, we examine bilateral migration flows between one country and the rest of the world. To this end, we develop a formal model that assumes rational individuals and which is partly based on insights from the micro-theory of migration. In doing so, we include human development and distinguish between regular and aysl-related migration. We test the model empirically on the example of Germany. It turns out that climate change and life expectancy have a significant impact on migration. Contrary to our expectations, the economic development, the extent of social assistance and the level of education do not seem to have any significant influence. With our paper, we expand previous research on migration with an empirically based model.

This study explores the effects of monetary transaction costs on economic growth in a closed overlapping generations economy with cash-in-advance constraints. Working generations can also hold interest-bearing capital claims. Economic growth is powered by an engine of learning-by-doing and knowledge spillover among workers. The results indicate that reductions in transaction costs raise the balanced growth rate and possibly reduce long-term inflation and nominal interest rates.

Flooding poses significant costs to communities and is expected to vary in intensity and severity in the future. Previous research has shown that major flooding events significantly affect housing markets; however, perceptions of non-destructive flooding events have not been adequately studied. In this paper, I examine the housing price capitalization of elevated river levels that did not reach the major flood stage to measure their influence on flooding risk perceptions. Estimates from a property fixed effects hedonic model provide evidence that housing prices respond heterogeneously to non-destructive flooding, with a negative and significant effect in the 100 year floodplain, but not the 500 year floodplain or other areas. These results show that a major event is not necessary for residents to update their beliefs and can inform future extreme natural event policy.

This study investigates the financial development and remittances nexus using a panel of 84 countries at all levels of income over the 1995 to 2018 period. We employ a dynamic commonly correlated effects estimator (DCCE) for a heterogeneous panel data model with weakly exogenous regressors to investigate the impact of financial development on remittances using indices that cover all aspects of the financial sector development (overall, institutional, and markets). The results indicate the importance of the development of the financial sector for remittance inflows, regardless of the motives. Our findings generally support the notion that improving the financial sector positively influences the magnitude of remittances for lower-income countries but not high-income countries. To attract more remittances, policymakers of low-income countries may implement policies that improve the development of the financial sector.

The main motivation of this paper is to use machine learning techniques to build a new insolvency risk rating metric for banks traded on Brazilian stock exchange. Then, a set of prediction models will be used to project the risk rating of these institutions. Conventionally, the literature analyzes bank insolvency risk from accounting data and macroeconomic variables. In addition to these variables, this paper will construct a series of bank institution manager sentiment, via quarterly reports (ITR), and this will be used to improve the accuracy of bank risk predictions. The results indicate that the bank risk classification, via the k-means algorithm, was able to classify 17% of the sample into the highest risk group (1), while 83% of the sample was in the lowest bankruptcy risk group (0). Using the Z-score metric, we found that 65% of the sample is in the low-risk group, and 35% of the sample is in the high-risk group. Thus, the k-means algorithm is more rigorous in classifying a bank in the highest risk category. Next we used the data already described to project the risk of bank insolvency. The results of this step showed that the decision tree model performed the best for the test sample. In addition, it was found that the inclusion of the bank sentiment variable was able to improve the performance of the prediction models, especially, when bank sentiment is constructed from a time-varying dictionary.

A detailed examination of wage data points to a wage polarization trend vis-à-vis the distribution of qualifications. Theoretically terms, this points to the need for modeling focused on the relevance of the direction of technological knowledge. To this end, we branched production into routine and non-routine tasks. In this way, the results produced positive relationships between the relative supply of skilled workers and the skill premium and between automation and wage polarization.

Antisocial behavior experiments, both conducted in the laboratory or in the field, have become commonplace in the experimental economics literature. Such experiments found their relevance in the real world as people are not always selfish or nice to others, but they also sometimes behave spitefully. This paper focuses on payoff-destruction experiments conducted over the last two decades and synthesizes the findings. We are able to find 46 studies where we found inequity reduction and pure spite as the main motives for such behavior. This behavior can also be explained by conflict experience. We conclude with suggestions for future research.