JOURNAL OF QUANTITATIVE ECONOMICS最新文献

Abstract

In this article, I address the question of who crosses the border into the United States for the purpose of giving birth, and how these patterns may have changed over time. This work is the first timely, quantitative analysis of its kind for the United States. Decreased medical tourism for the purpose of giving birth during the Trump era has implications on other secondary medical effects of that administration, as well as for how the makeup of the United States population is likely to change. In terms of methodology, I employ data from the 2014–2020 United States Neo-Natality Survey to examine all births in the United States during that time. Ordinary Least Squares (OLS) and, alternatively, a Probit regression analysis, are employed. I find that putative birth medical tourism decreased dramatically during the Trump administration. Additionally, individuals who come for the purpose of giving birth were generally healthier, higher SES, and more likely to be Hispanic. The findings presented here may be important for informing current and future immigration and medical tourism policies.

Monetary policy and its transmissions have been debated by various schools of thought. The purpose of this paper is to empirically tests whether monetary policy has supply side effect influencing Indian economy’s total factor productivity. This study uses ARDL model to ascertain the long run relationship between monetary policy proxies and total factor productivity (TFP). Cointegration tests reveal that total factor productivity has a relationship with all of the monetary policy proxies. The ARDL results reveal a negative relationship between TFP and some monetary policy proxies in the short run, but a positive effect in the long run. These results showcase the possible supply side transmission of monetary policy in India, which can help in determining an optimal policy so as to augment TFP, an important driver of economic growth. The study only focusses on the Indian economy and spillover effects of other Asian economies on India’s TFP can also be examined.

Abstract

Using data for 1992–2020, the paper assesses the role of elections on liquidity hoarding by Indian commercial banks. The findings reveal that liquidity hoarding typically increases during election years, driven primarily by an increase on the asset side of their balance sheet. Such behaviour manifests mainly for public and private banks and much less for foreign banks. The evidence also indicates a cyclical pattern in the evolution of liquidity hoarding, such that it increases in the run-up to the elections.

This study investigates the effects of economic policy uncertainty (EPU) and geopolitical risks (GPR) originating from various destination economies on the export demand facing a developing economy, i.e., India. We employ monthly panel data on exports from India to 29 economies spanning January 2015 to December 2019. For analysis, we use a range of estimators that address potential econometric issues such as non-stationarity, serial correlation, cross-sectional dependence, and different lag orders and breaks in error processes. Our results suggest adverse and sizeable effects of destinations’ EPU and GPR on the export revenues of India. We also find that income, relative inflation, and the exchange rate serve as channels via which uncertainty affects exports. Our evidence is novel and helps further the available body of knowledge on the impact of economic and geopolitical uncertainties on developing economies through an established channel, i.e., export.

Using a Ricardo model, this study aims to assess the impact of climate change on agricultural incomes in northern Cameroon. The data used comes from a survey of 450 farming households in 23 villages. The results indicate that a 1-mm increase in rainfall leads to an increase of 12.68 dollars in farm income per hectare in summer, 0.92 dollars in winter, 9.59 dollars in spring and 13.30 dollars in autumn. On the other hand, a 1 °C increase in temperature leads to a decrease in net farm income per hectare of 3.54 dollars in summer, 1.26 dollars in winter, 3.40 dollars in spring and 6.11 dollars in autumn. In addition, the hypothesis of a non-linear relation has been validated. An increase in autumn temperatures benefits net farm income up to a maximum point, after which very high temperatures begin to be harmful to crop growth and productivity and consequently reduce farm income. Concerning precipitations, autumn and summer rainfall significantly positively affect net farm income up to a certain maximum point, after which the excess becomes harmful to crops. Furthermore, the study found that farm income is more sensitive to precipitation than to temperature. The policy implications of these findings are equally discussed.

A rich variety of threshold regression models have been in use starting with Tobin (1978). However, several applications indicate the necessity for a class of threshold regression models that have not been considered so far. This note presents a specification of such models and offers a novel method of estimation.

This paper uses Rao’s Quadratic Entropy (RQE), a general measure of diversity of population, to analyze portfolio diversification. We provide both theoretical and empirical evidence that RQE is a valid, flexible and unifying approach for quantifying and managing the benefits of portfolio correlation diversification.