The stabilizing effect of social distancing: Cross-country differences in financial market response to COVID-19 pandemic policies

This paper develops a model to assess the quantitative effects of entry costs and financial frictions on cross-country income and total factor productivity (TFP) differences, with a primary focus on the interaction between entry costs and financial frictions. The model is calibrated to match the establishment-level statistics for the U.S. economy, assuming a perfect financial market. The simulations based on the calibrated model show that entry costs and financial frictions together account for 55% and 46% of the cross-country variation in output and TFP in the data. Moreover, a substantial portion of the variation is accounted for by the interaction between entry costs and financial frictions. The main mechanism is that financial frictions amplify the effect of entry costs.

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Turbulence in the financial markets: Cross-country differences in market volatility in response to COVID-19 pandemic policies

10.31234/osf.io/58u7c ◽

2020 ◽

Author(s):

Steven J Bickley ◽

Ho Fai Chan ◽

Benno Torgler ◽

Richard Colthurst ◽

Martin Brumpton

Keyword(s):

Financial Markets ◽

Financial Market ◽

Government Policy ◽

Structural Breaks ◽

Market Volatility ◽

Creative Commons ◽

Health And Wellbeing ◽

Policy Interventions ◽

Country Differences ◽

Cross Country

COVID-19 has had far-reaching global effects on the health and wellbeing of individuals on every continent. The economic and financial market response has been equally disastrous with high levels of volatility. This study explores temporal relations between structural breaks, market volatility and government policy interventions for 28 countries and their respective financial market indices.File description:Scripts:breaks.do – test for the unknown structural breaks in the turnover data.turnover.do – merge the mobility dataset (change in mobility to residential), stay-at-home policy, COVID stats, and turnover. It also generates the dataset for the R code (should upload yours) and the rest of the analysis.hurstexponent.R - estimates/calculates log returns, performs STL Decomposition and MFDFA analysis. Data:mobility.dat - Google mobility databloomberg_turnover.dat - Raw traded value from Bloombergturnover.do - merged traded value datacsse.dat - COVID-19 statisticsPlease contact [email protected] for questions and refer to our accompanying paper. Recommended Citation: TBAData use policy: Creative Commons Attribution CC BY standard.

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How Does Firm Size Explain Cross-Country Differences in Ownership Concentration?

SSRN Electronic Journal ◽

10.2139/ssrn.3547092 ◽

2020 ◽

Author(s):

Fariborz Moshirian ◽

Nguyen Thi Thuy ◽

Jin Yu ◽

Bohui Zhang

Keyword(s):

Firm Size ◽

Ownership Concentration ◽

Country Differences ◽

Cross Country

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COVID-19 Pandemic: Social Distancing, Public Policy, and Market Response

SSRN Electronic Journal ◽

10.2139/ssrn.3593813 ◽

2020 ◽

Author(s):

Krista J. Li ◽

Xi Li

Keyword(s):

Public Policy ◽

Market Response ◽

Social Distancing

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Connections Between Cultures: Using Empirical Distributions for Measuring Cultural Differences

Journal of Cross-Cultural Psychology ◽

10.1177/0022022120982370 ◽

2020 ◽

pp. 002202212098237

Author(s):

Wolfgang Messner

Keyword(s):

Cultural Values ◽

Cultural Differences ◽

Distance Measures ◽

Cultural Variation ◽

Group Level ◽

Psychological Phenomena ◽

Empirical Distributions ◽

Leibler Divergence ◽

Country Differences ◽

Cross Country

The past few decades have seen an explosion in the interest in cultural differences and their impact on many aspects of business management. A noticeable feature of most academic studies and practitioner approaches is the predominant use of national boundaries and group-level averages as delimiters and proxies for culture. However, this largely ignores the significance that intra-country differences and cross-country similarities can have for identifying psychological phenomena. This article argues for the importance of considering intra-cultural variation for establishing connections between two different cultures. It uses empirical distributions of cultural values that occur naturally within a country, thereby making intracultural differences interpretable and actionable. For measuring cross-country differences, the Gini/Weitzman overlapping index and the Kullback-Leibler divergence coefficient are used as difference measures between two distributions. The properties of these measures in comparison to traditional group-level mean-based distance measures are analyzed, and implications for cross-cultural and international business research are discussed.

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