Underemployment in Australia: a panel investigation

This 2001–2013 panel study finds 33% of part-time employees to be underemployed, disproportionately affecting males, immigrants, youth, the blue-collared and new to our study, those on casual contracts. Within the underemployed sample, we report that the gap between preferred and actual hours (working hour tension) also varies by personal and labour characteristics, largely consistent with that found for the determinants of underemployment. The continued growth of part-time employment and casualization in recent years has been more pronounced among males, raising their rates of underemployment as they disproportionately prefer to work more hours vis-à-vis their part-time female peers.     

Risk-Taking Behavior and Capital Adequacy in a Mixed Banking System: New Evidence from Malaysia Using Dynamic OLS and Two-Step Dynamic System GMM Estimators

This study is the first attempt to investigate the relationship between the level of risky assets and capital level in a mixed Malaysian banking system covering 83 months starting December 2006. The results of dynamic ordinary least squares indicate positive relationship between capital ratio (CAR) and risk-weighted asset ratio (RWA) in the long run. Furthermore, the causality analysis based on panel vector error correction model (VECM) and two-step dynamic system generalized method of moments indicates unidirectional causality from CAR to RWA. Our results further suggest that higher capital growth and capital buffer provide an extra cushion for the Malaysian banks to pursue relatively riskier financial activities, and the nature of risk-taking behavior of Islamic banks follows that of the conventional banks.     

A Comparison of Consensus and BVAR Macroeconomic Forecasts

This paper provides a one-month-ahead, macroeconomic, Bayesian Vector Autoregressive (BVAR) forecasting approach that offers several advantages over conventional short-term forecasting procedures. In particular, it produces more accurate forecasts than the Bloomberg consensus forecasts, on average, for 20 major macroeconomic variables. In addition to a quantitative comparison of BVAR and Bloomberg consensus forecast, the paper focuses on five important areas of macroeconomic forecasting: the role of short-term macroeconomic forecasting, the importance of a robust forecasting approach, the importance of timing of data releases, forecast evaluation criteria, and the importance of changing model specifications as conditions warrant.     

The Deeper the Recession,the Stronger the Recovery: Is It Really That Simple?

Are deep recessions typically followed by strong recoveries? This paper investigates this question. There is not a single standard definition for a deep recession or a strong recovery. Therefore, our first step is to define what constitutes a deep recession and a strong recovery. Next we examine whether there is any causal relationship between deep recessions and strong recoveries. Our analysis shows there is no relationship between the depth of a recession and the subsequent pace of economic recovery when we use Gross Domestic Product, Gross Domestic Income, and employment as measures of recession and recovery. A modestly significant relationship does exist, however, between the magnitude of increases in the unemployment rate during a recession and decreases in the unemployment rate during the ensuing recovery.     

Trade and Specialisation in Pollution Intensive Industries: North–South Evidence

Abstract

The pollution haven hypothesis (PHH) and the capital-labour hypothesis (KLH) state that the relative level of a country's environmental regulations and capital and labour endowments determines its comparative advantage respectively. Since these hypotheses lead to conflicting predictions as to whether the North or the South will specialise in pollution-intensive production, this paper examines whether changes in trade and specialisation patterns allow us to distinguish between pollution haven and factor endowment effects. We employ a methodology that enables us to present North-South trade patterns over time and to identify those periods when trade patterns were consistent with either the PHH and/or the KLH as a foundation for undertaking more detailed econometric studies.     

A New Framework to Estimate the Near-Term Path of the Fed Funds Rate

We propose a forward-looking method to estimate the path for the federal funds target rate. We utilize six-month out probabilities of inflationary and disinflationary pressures, along with a labor market index, to estimate the fed funds rate. We further suggest that due to the changing nature of economies and impending risks to the economic outlook, a time-varying method (consistent with the nature of risks) would help decision makers to improve effective decision making. Our econometric results suggest disinflation (or disinflationary pressure), not inflationary pressure, best explains fed funds rate movements from the 1990s forward. Based on June 2016 data, there is a 55 percent chance that the inflation rate would stay below 1.5 percent during the next six months. The recent higher disinflationary pressure probability may be one reason the FOMC has repeatedly lowered its path for the fed funds rate. Unfortunately, the low-inflation zombie is real.     

Is Predicting Recessions Enough?

We propose an ordered probit framework to simultaneously predict the probabilities of recession, weaker recovery, and stronger recovery. Our approach helps identify (a) whether the next phase is a recession, (b) when the recovery period starts, and (c) whether the recovery would be a weak or strong one compared to historical standards. We believe our approach would help policy makers decide when would be appropriate to (1) start expansionary policies (higher probabilities of recession), (2) continue expansionary policies (higher probabilities of weaker recovery), or (3) turn to neutral/contractionary policies (higher probabilities of stronger recovery). The ordered probit model shows the probabilities of recession staying above 50 percent during all five recessions in our simulated out-of-sample analysis of 1980:Q1–2016:Q1. The probabilities of weaker recovery are consistent with actual periods of below trend growth. Based on 2016:Q1 data, the model suggests a meaningfully higher chance of continuing below trend growth. One key result is that the probability of weaker growth has been persistently higher than the other two scenarios for the past several years. These higher probabilities of weak growth are consistent with the accommodative monetary policy stance of the past eight years.     

Global estimates of growth–inequality–poverty (GIP) triangle: evidence from World Bank’s classification countries

This study extended the concept of ‘growth–inequality–poverty (GIP) triangle’ by using the principle component approach which allows us to composite different poverty and inequality indicators into one single index that contains most of the useful information from the original dataset. Using the idea of GIP triangle, this study examines the long-run relationship among weighted poverty index (which comprises headcount ratio, poverty gap and squared poverty gap); weighted inequality index (i.e., Watts Index, Gini Index and MLD Index) and average monthly per capita income in the designated 138 countries according to World Bank’s classification over a period of 2005–2010. The data set mainly contain countries’ unit record household survey at least one which is conducted between the countries during the sample period. The regression model encompassing the impact of economic growth and income inequality on poverty reflects that income inequality increases poverty while economic growth decreases poverty. It indicates that the impact of inequality in increasing poverty is a somewhat greater than that of growth in average income in reducing overall poverty in a sample countries. The other regression model encompassing the impact of economic growth and poverty on income inequality showed that the poverty itself is also likely to be a barrier for poverty reduction; and inequality seems to predict lower future growth rates. The final regression model depicting the impact of poverty and income inequality on mean income of the household suggests that poverty itself reduces mean income of the household while income inequality increases economic growth. The results are interesting and simply suggest that whenever social institutions malfunction, the incidence of damage would usually be distributed unevenly over the society’s members.     

Estimating the economic cost of the COVID-19 pandemic

Business Economics - Our study presents a framework to estimate economic costs of the COVID-19 pandemic for the U.S. economy. We characterize whether the pandemic-related damages are short-lived or...