A recession‐and‐state forecasting model

The state forecasting model (SFM) developed herein predicts the probability that a recession will begin or end within the next quarter. It is also important to forecast the state, as models prone to false alarms are not useful. The model combines parsimony, predictive accuracy, and ease of estimation using readily available data. No regressor is benchmark‐revised, and only one is seasonally adjusted. The SFM correctly forecasts, out‐of‐sample, the binary state in 163 of 164 quarters for an overall proportion of correct forecasts of 0.994. The results demonstrate the discriminating ability, longevity and striking forecasting ability of the model. A benchmark model based on the newly revised Leading Economic Index of the Conference Board has zero marginal predictive power in the presence the SFM.     

A Meta‐Analysis of the Investment‐Uncertainty Relationship

In this article we use meta‐analysis to investigate the investment‐uncertainty relationship. We focus on the direction and statistical significance of empirical estimates. Specifically, we estimate an ordered probit model and transform the estimated coefficients into marginal effects to reflect the changes in the probability of finding a significantly negative estimate, an insignificant estimate, or a significantly positive estimate. Exploratory data analysis shows that there is little empirical evidence for a positive relationship. The regression results suggest that the source of uncertainty, the level of data aggregation, the underlying model specification, and differences between short‐ and long‐run effects are important sources of variation in study outcomes. These findings are, by and large, robust to the introduction of a trend variable to capture publication trends in the literature. The probability of finding a significantly negative relationship is higher in more recently published studies.     

The Short‐ and Long‐Run Determinants of Less‐Educated Immigrant Flows into U.S. States

We use a gravity model of migration and alternative estimation strategies to analyze how income differentials affect the flow of immigrants into U.S. states using annual data from the American Community Survey. We add to existing literature by decomposing income differentials into short‐ and long‐term components and by focusing on newly arrived less‐educated immigrants between 2000 and 2009. Our sample is unique in that the vast majority of our observations take zero values. Models that include observations with zero‐flow values find that recent male immigrants respond to differences in (short‐term) GDP fluctuations between origin countries and U.S. states, and perhaps to (long‐term) trend GDP differences as well. More specifically, GDP fluctuations pull less‐educated male immigrants into certain U.S. states, whereas GDP trends push less‐educated male immigrants out of their countries of origin. Effects for less‐educated women are less robust, as GDP coefficients tend to be much smaller than for men.     

Revisiting Growth‐Poverty Relationship: A Medium‐Term Causality Approach

This article examines the potential medium‐term causal relationship between changes in Gross Domestic Product (GDP) per capita and poverty in developing countries during the 1970s–1990s. For this purpose, we use panel data model evaluation techniques to test the out‐of‐sample forecasting performance of competing models. We conclude that the evidence supports the hypothesis that increases in GDP per capita cause unidirectional poverty reduction, measured by the $1/day poverty rate, in the period 1970s–1980s. The results are similar when analysing low‐ and middle‐income countries and mid‐high‐ and very high‐inequality countries separately. However, in the period 1980s–1990s, it is only statistically significant for low‐income countries.     

Teaching Preparation and Placement in “Non‐top‐tier” Ph.D. Programs

In a recent article, Jacobson (2015) provides an invaluable economics job market guide for economics Ph.D. candidates from “non‐top‐tier” programs in the United States. Her treatment is detailed and, to a large extent, thorough. However, Jacobson fails to discuss the development of effective lead teaching experience in graduate school as a (potentially central) aspect of job market preparation. In the present comment, we develop and summarize a job posting and placement data set that focuses on Ph.D. candidates from non‐top‐tier programs. The data strongly suggests that the development of lead teaching experience in graduate school, rather than an optional line on one's vita, is an often pivotal element of realized job placement for Ph.D. candidates of non‐top‐tier programs. These findings corroborate with List's (2000) finding that, “a candidate's teaching portfolio was highly influential in the academic market” (p. 197). We also discuss the acquisition of lead teaching experience and benefits of early teaching experience that may extend beyond first job placement.     

IMPLEMENTING A ROBUST RISK MODEL FOR SOUTH AFRICAN EQUITY MARKETS: A PEAK‐OVER‐THRESHOLD APPROACH

This paper implements a market risk model for the South African equity market using daily returns of the Johannesburg Stock Exchange All Share Index. Firstly, we separate positive returns from negative returns and model them using the peak‐over‐threshold (POT) method in order to compute the downside as well as upside risk measures separately. We thereafter compute the value‐at‐risk (VAR) and the expected shortfall (ES) estimates corresponding to upside and downside risks. We bootstrap these risk measures and compute their standard errors and confidence intervals (CIs) to see whether they fall inside these CIs. Secondly, we compute out‐sample forecasts of VAR estimates using the POT method and the generalised autogressive conditional heteroscedasticity process. Three backtesting methodologies are employed: the unconditional and conditional coverage tests and the counting of number of exceptions according to Basel II green zone. We find that all our VAR and ES estimates are well inside their CIs and that at lower quantiles, parametric ES estimates are equal to POT‐ES estimates, although the difference between the two is more pronounced at higher quantiles (99% or higher). Furthermore, our market risk model falls into the Basel II green zone, as it produces fewer exceptions in out‐sample space.     

Modelling Intercontinental Tourism Consumption in South Africa: A Systems‐of‐Equations Approach

This paper investigates the pattern of inbound tourists' consumption in South Africa, examining four main intercontinental markets and five different tourism goods. The empirical investigation develops an almost ideal demand system (AIDS) model and it extends recent research by allowing tourists to base their spending decision on the real effective price differences between South Africa and their home country. The results show that tourist spending in South Africa is a luxury good, and tourists react normally to a change in the relative price of goods. The cross‐price elasticities suggest that the preferences of different markets influence their view of substitutability and complementary effects between various products in South Africa.     

Exchange Rate Pass‐through to China's Export Price: A Product‐level Investigation

Exchange rate movement usually results in changes in the production costs of exporting firms, and, therefore, the prices and the quantity of traded products. The present paper constructs a theoretical model to demonstrate that export products with higher productivity, or with larger market share, or of higher quality will experience a less complete pass‐through. Using the six‐digit harmonized system export data from the CEPII database over the period of 2000 to 2013, the present paper examines how product heterogeneity affects the exchange rate pass‐through of Chinese exports. The empirical results show that the most competitive Chinese export products, or those least affected by exchange rate risks, are those of higher quality, with higher technological complexity and at the high end of the international value chain. Therefore, Chinese exporting firms should pay more attention to improving export quality and upgrading technology to better cope with exchange rate risks and to enjoy more bargaining power in the international market.