Real exchange rate misalignment and business cycle fluctuations in the Asia-Pacific

Real exchange rate (RER) misalignment, which is the deviation between the actual real exchange rate from its equilibrium, occurs frequently among developing countries. Studies have shown that RER misalignment may have negative economic implications, such as a decline in economic growth, exports, and export diversification and an increased risk of currency crises and political instability. Using quarterly data for 22 sample countries from 1990 to 2018, this paper investigates the impact of RER misalignment on business cycles in the Asia-Pacific by employing a panel vector autoregression involving consumer price index (CPI) inflation, output gap, short-term interest rates, and RER misalignment. We find that RER overvaluation may reduce CPI inflation and short-term interest rates. We also find that the Asia-Pacific region is highly heterogeneous in that the output gaps of some countries, particularly from the Southeast Asian region, are more susceptible to RER misalignment shocks.     

Organizational ambidexterity and financial performance in the banking industry: evidence from a developing economy

Journal of Financial Services Marketing - The paper examined the relationship between organizational ambidexterity on the attitude of employees and the financial performance of the banking sector...     

The power of online panel paradata to predict unit nonresponse and voluntary attrition in a longitudinal design

The objective of this study is to identify factors affecting participation rates, i.e., nonresponse and voluntary attrition rates, and their predictive power in a probability-based online panel. Participation for this panel had already been investigated in the literature according to the socio-demographic and socio-psychological characteristics of respondents and different types of paradata, such as device type or questionnaire navigation, had also been explored. In this study, the predictive power of online panel participation paradata was instead evaluated, which was expected (at least in theory) to offer even more complex insight into respondents’ behavior over time. This kind of paradata would also enable the derivation of longitudinal variables measuring respondents’ panel activity, such as survey outcome rates and consecutive waves with a particular survey outcome prior to a wave (e.g., response, noncontact, refusal), and could also be used in models controlling for unobserved heterogeneity. Using the Life in Australia? participation data for all recruited members for the first 30 waves, multiple linear, binary logistic and panel random-effect logit regression analyses were carried out to assess socio-demographic and online panel paradata predictors of nonresponse and attrition that were available and contributed to the accuracy of prediction and the best statistical modeling. The proposed approach with the derived paradata predictors and random-effect logistic regression proved to be reasonably accurate for predicting nonresponse—with just 15 waves of online panel paradata (even without sociodemographics) and logit random-effect modeling almost four out of five nonrespondents could be correctly identified in the subsequent wave.

     

Deep order flow imbalance: Extracting alpha at multiple horizons from the limit order book

We employ deep learning in forecasting high-frequency returns at multiple horizons for 115 stocks traded on Nasdaq using order book information at the most granular level. While raw order book states can be used as input to the forecasting models, we achieve state-of-the-art predictive accuracy by training simpler “off-the-shelf” artificial neural networks on stationary inputs derived from the order book. Specifically, models trained on order flow significantly outperform most models trained directly on order books. Using cross-sectional regressions, we link the forecasting performance of a long short-term memory network to stock characteristics at the market microstructure level, suggesting that “information-rich” stocks can be predicted more accurately. Finally, we demonstrate that the effective horizon of stock specific forecasts is approximately two average price changes.     

Dynamics of contention in the gig economy: Rage against the platform,customer or state?

Protest in the gig economy has taken many forms and targets (platforms, customers and state officials). However, researchers are yet to adequately account for this diversity. We use a European survey of Upwork and PeoplePerHour platform workers to investigate worker orientation towards different forms of protest. Results reveal that worker anger, dependence and digital communication shape contention in the remote gig economy. Support for collective organisation is associated with anger at platforms as well as their dependence on the platform and communication with other workers. Individual action against clients is associated with anger and communication but not dependence. Support for state regulation is associated only with anger but not dependence or communication. We conclude that the relational approach entailed by Mobilisation Theory can aid explanation in the gig economy by shedding light on the dynamic process by which solidarity and dependence alter the perceived cost/benefits of particular remedies to injustice.     

Reverse Immigration Effects for Expatriates in Oman During the COVID-19 Pandemic Shock

The COVID-19 pandemic produced dramatic aftershocks throughout the global labor markets with rapid changes in differential employment opportunities. Labor market disruptions were sparked by the pandemic in Oman, where expatriates live and work. For the first time, the analysis investigates certain hypotheses relevant to the Aspirations-Capabilities framework and whether these hypotheses survive the pandemic exogenous shock. More specifically, testing these hypotheses, the analysis investigates whether the COVID-19 pandemic shock had a negative impact on expatriates in the host country, as well as it identifies heterogeneous effects among different ethnic groups. Using Datastream data, this analysis investigates the sudden drop in ethnic expatriates in Oman using ordinal least squares and instrumental variable estimations. A steeper decline in the expatriate employment rate reflects a disproportionately adverse impact that the initial phase of the COVID-19 pandemic had on immigrant employment. The findings identify substantial ethnic differences when reverse immigratory effects are exhibited.

     

Status and mortality: Is there a Whitehall effect in the United States?

The influential Whitehall studies found that top-ranking civil servants in Britain experienced lower mortality than civil servants below them in the organizational hierarchy due to differential exposure to workplace stress. I test for a Whitehall effect in the United States using a 1930 cohort of white-collar employees at a leading firm – General Electric (GE). All had access to a corporate health and welfare program during a critical period associated with the health transition. I measure status using position in the managerial hierarchy, attendance at prestigious management training camps and promotions, none of which is associated with a Whitehall-like rank-mortality gradient. Instead, senior managers and executives experienced a 3–5-year decrease in lifespan relative to those in lower levels, with the largest mortality penalty experienced by individuals in the second level of the hierarchy. I discuss generalizability and potential explanations for this reversal of the Whitehall phenomenon using additional data on the status and lifespan of top business executives and US senators.     

Manufacturing output and extreme temperature: Evidence from Canada

This paper analyzes the effects of extreme temperature on manufacturing output using a data set covering the universe of manufacturing establishments in Canada from 2004 to 2012. Extreme temperature can affect manufacturing activity directly through its impact on labour productivity and indirectly through a change in demand for products. Using a panel fixed effects method, our results suggest a non-linear relationship between outdoor extreme temperature and manufacturing output. Each day where outdoor mean temperatures are below $-18$ °C or above 24 °C reduces annual manufacturing output by 0.18% and 0.11%, respectively, relative to a day with mean temperature between 12 ° and 18 °C. In a typical year, extreme temperatures, as measured by the number of days below $-18$ °C or above 24 °C, reduce annual manufacturing output by 2.2%, with extreme hot temperatures contributing the most to this impact. Given the predicted change in climate for the mid- and end of century, we predict annual manufacturing output losses due to extreme temperature to range between 2.8% and 3.7% in mid-century and 3.7% and 7.2% in end of century.     

Share repurchases on trial: Large-sample evidence on share price performance,executive compensation,and corporate investment

Using a large sample of US stocks covering more than three decades, we empirically examine common criticisms of and rationales for stock repurchases. Repurchases account for a tiny fraction of the trading volume in a typical stock, making their price impact too small to generate short-term price manipulation. Price appreciation following repurchases is modest and does not reverse on average, suggesting the small price increases following repurchases signal firms’ good prospects. Also, we find no evidence that CEOs of repurchasing firms are paid excessively or that repurchases crowd out valuable investment opportunities. Because repurchases do not appear to be systematically abusive, enforcement action should be sufficient to deal with any bad actors, and significant regulation seems unwarranted.