Institutional investors and cross-border mergers and acquisitions: The 2000–2018 period

Using a sample of mergers and acquisitions (M&As) from 26 countries over 2000–2018, we find that domestic institutional investors facilitate both domestic and cross-border M&As. The facilitation effect is more pronounced for domestic than cross-border M&As. When the acquirer country has greater financial freedom or better investor protection than the target country, domestic institutional investors facilitate cross-border M&As more effectively. As Ordinary Least Squares regressions are not the best approach regarding cross-border M&As, we confirm that the main results are robust to Zero-inflated Poisson regressions. Foreign institutional investors' influence on cross-border M&As is stronger when the sample excludes the United States.     

“Modeling the impact of wars and terrorism on tourism demand in Kurdistan region of Iraq”

Portuguese Economic Journal - Recent political instabilities in the Middle East have led to strong negative impacts on the tourism sector. The aim of this study is to investigate the extent and the...     

How environmental innovation influences firm performance: A meta-analytic review

Coupled with the increasing concern toward sustainability and sustainable development issues, environmental innovation practices have been of burgeoning interest among both scholars and practitioners. Building on this, the main purpose of this study is to quantitatively aggregate the extant empirical research on eco-innovation and firm performance and to assess the role of moderating factors in this theoretical relationship by pursuing a meta-analytic approach. To serve this objective, 196 effects based upon 70 studies including more than 25,000 firms (N = 25,412) were meta-analytically examined. Quantitative evidence drawn from the meta-analysis indicates that organizational eco-innovation exerts the strongest influence on firm performance. Moreover, the meta-analytic findings suggest that significant variations in the correlation between eco-innovation and firm performance exist across different performance types, and the magnitude of the eco-innovation–firm performance association is stronger in developing compared with developed countries. This meta-analytic review is expected to considerably contribute to the pertinent literature by means of improving the understanding of the relevance of eco-innovation typology to firm performance.     

Forecasting Turkey’s Credit Ratings with Multivariate Grey Model and Grey Relational Analysis

The concept of credit rating rooted back to mid-nineteenth century has become one of the most important elements in the world economy together with the globalization period gradually accelerating in the last two decades and increasing the interaction and sensitivity in the international markets. With the globalization and deepening in the financial markets; the effect, reliability and stability of knowledge of the actors who are in charge for directing the global capital flows have quite a big importance in terms of the decisions to be made in the future. In this process, credit rating agencies eliminating the information asymmetry between the countries and institutions who want to create financial resource by borrowing from the savings owners and foreign institutions. Credit ratings determined by the mentioned organizations are accepted as an indicator of the countries to meet the financial obligations in other words their creditworthiness. For Turkey’s economy having a structure with a high level of external financing needs in terms of accelerating the growth and development process, it is inevitable to have an international creditworthiness increasing long-term investment tendency meeting foreign capitals’ trust search. In this study, firstly the determinants of the credit ratings given by credit rating agencies are determined and then forecasting Turkey’s future credit ratings by combining them with multivariate grey model and grey relational analysis are performed.

     

The Japanese saving rate between 1960 and 2000: productivity,policy changes,and demographics

In this paper, we use an overlapping generations model to study the factors generating the saving rate in Japan between 1960–2000. The model economy allows for observed aging of the population, total factor productivity (TFP), and fiscal policy to affect the national saving rate. Our calibrated general equilibrium setup generates saving rates that are reasonably similar to the data during this period. Our counterfactual experiments indicate that observed TFP growth rates are the main reason for both the secular decline and the two humps in the saving rate during 1960–2000.      

A life cycle analysis of social security

Summary We develop an applied general equilibrium model to examine the optimal social security replacement rate and the welfare benefits associated with it. Our setup consists of overlapping generations of 65-period lived individuals facing mortality risk and individual income risk. Private credit markets, including markets for private annuities, are closed by assumption. Unlike previous analyses, we find that an unfunded social security system may well enhance economic welfare. In our benchmark economy, the optimal social security replacement rate is 30%, and an empirically more plausible replacement rate of 60% raises welfare compared with an economy with no social security system.We would like to thank Andy Atkeson, V. V. Chari, Steve Davis, Paul Evans, Lars Hansen, Tim Kehoe, Nobu Kiyotaki, Ed Prescott, José-Victor Ríos-Rull, Richard Rogerson, Tom Sargent, Nancy Stokey, Dick Sweeney, Robert Townsend, and the participants of the NBER Economic Fluctuations Small Group Workshop on Micro and Macro Perspectives on the Aggregate Labor Market in Palo Alto, the NBER General Equilibrium Theory Conference in Minneapolis, the Money and Banking Workshop at the University of Chicago, and the NBER Summer Institute. An earlier version of this paper was titled A Dynamic Stochastic General Equilibrium Analysis of Social Security. This material is based upon work supported by the National Science Foundation under Grant No. SES-9210291. We also thank the Minnesota and San Diego Supercomputer Centers for their support.