Good signals gone bad: Dynamic signalling with switched effort levels

This paper examines signalling when the sender exerts effort and receives benefits over time. Receivers only observe a noisy public signal about the effort, which has no intrinsic value.The modelling of signalling in a dynamic context gives rise to novel equilibrium outcomes. In some equilibria, a sender with a higher cost of effort exerts strictly more effort than his low-cost counterpart. The low-cost type can compensate later for initial low effort, but this is not worthwhile for a high-cost type. The interpretation of a given signal switches endogenously over time, depending on which type the receivers expect to send it.     

A new look at variation in employment growth in Canada: The role of industry,provincial, national and external factors

We examine fluctuations in employment growth using Canadian data from 1976 to 2010. We consider a wide range of models and examine the sensitivity of our findings to modelling assumptions. The results from our most preferred model, which we selected using the Bayesian Information Criteria, indicate that most of the variance in employment growth that is not due to the idiosyncratic error comes from domestic sources, with most of this coming from industry and provincial factors. Overall, we find that external and national factors play a much smaller role in employment fluctuations than in earlier research. We provide some possible explanations for these differences and discuss the implications of our findings for public policy and theory.     

Forecasting macroeconomic variables in emerging economies

Forecasting macroeconomic variables in rapidly changing emerging economies presents a number of challenges. In addition to structural changes, the time-series data are usually available only for a short number of periods, and predictors are available in different lengths and frequencies. Dynamic model averaging (DMA), by allowing the forecasting model to change dynamically over time, permits the use of predictors with different lengths and frequencies for the purpose of forecasting in a rapidly changing economy. This study uses DMA to forecast inflation and growth in Vietnam, Thailand, Philippines, Sri Lanka and Ghana. We compare its forecasting performance with a wide range of other time-series methods. We find that the size and composition of the optimal predictor set changed, indicating changes in the economic relationships over time. We also find that DMA frequently produces more accurate forecasts than other forecasting methods for both inflation and economic growth in the countries studied.     

How can investors build a better portfolio in small open economies? Evidence from Asia’s Four Little Dragons

This study investigates the role of hedging and portfolio design among stocks, exchange rates, and gold in small open economies (SOEs) from 4 January 2000 to 31 March 2020. We adopt the trivariate dynamic conditional correlation-fractionally integrated asymmetric power ARCH model and unconditional quantile regression model, and our findings show that the hedging role of the U.S. dollar (USD) and gold against stocks differs under regular and extreme market conditions. The USD can act as a powerful hedge asset for stocks in regular market periods. Moreover, during the global financial crisis and COVID-19 outbreak, the safe-haven effect of gold becomes stronger for almost all stocks, whereas the USD can serve as a strong safe haven against stock markets of Korea, Taiwan, and Singapore when stock returns are extremely low. In terms of portfolio designing, we find that adding the USD and gold to portfolios improves their hedging effectiveness, and the optimally weighted stock-USD-gold portfolio is the best portfolio strategy, irrespective of referring to return or risk.     

Noisy signaling in discrete time

This paper characterizes the equilibrium set of a dynamic noisy-signaling model in discrete time. A seller privately knows the quality of her asset. She can exert a costly effort to generate stochastic returns. Buyers stochastically arrive over time and, after observing the history of returns, they make price offers. In our model, the equilibrium behavior of the buyers is discontinuous: they only make acceptable (high) offers if the posterior about the quality is above a given threshold. As a result, the recursive nature of the model replicates the discontinuity, giving the equilibrium continuation payoff a complex self-replicating structure that may take the form of a devil’s staircase.     

On estimating long-run effects in models with lagged dependent variables

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.Our analysis points out the hazards of this practice. We use Monte Carlo experiments to demonstrate that estimating long-run impacts from dynamic models produces unreliable results.Biases can be substantial, sample ranges very wide, and hypothesis tests can be rendered useless in realistic data environments. There are three reasons for this poor performance. First, OLS estimates of the coefficient of a lagged dependent variable are downwardly biased in finite samples. Second, small biases in the estimate of the lagged, dependent variable coefficient are magnified in the calculation of long-run effects. And third, and perhaps most importantly, the statistical distribution associated with estimates of the LRP is complicated, heavy-tailed, and difficult to use for hypothesis testing. While many of the underlying problems have been long-known in the literature, the continued widespread use of the associated empirical procedures suggests that researchers are unaware of the extent and severity of the estimation problems. This study aims to illustrate their practical importance for applied research.     

Welfare costs of reclassification risk in the health insurance market

We assess the quantitative importance of reclassification risk in the US health insurance market. Reclassification risk arises because the health conditions of individuals evolve over time, while a typical health insurance contract only lasts for one year. Thus, a change in the health status can lead to a significant change in the health insurance premium. We measure welfare gains from introducing explicit insurance against this risk in the form of guaranteed renewable health insurance contracts. We find that in the current institutional environment individuals are well-sheltered against reclassification risk and they only moderately gain from having access to these contracts. More specifically, we show that employer-sponsored health insurance and public means-tested transfers play an important role in providing implicit insurance against reclassification risk. If these institutions are removed, the average welfare gains from having access to guaranteed renewable contracts exceed 4% of the annual consumption.     

Minimising emergency response time of ambulances through pre-positioning in Dhaka city,Bangladesh

This study conducted a large-scale survey in Dhaka, Bangladesh; the survey involved 95 major hospitals, more than 3000 emergency room patients, and 2 of the largest ambulance operators. Currently, most ambulances are parked within the vicinity of hospitals and are either dispatched or fetched by the acquaintances of the patient on demand, resulting in lengthy round trips. Reducing the response time of ambulances would certainly improve the emergency service, and pre-positioning of the ambulances could be a solution to reducing the response time. This study used two approaches to address the problem. First, the location-allocation problem was solved to find the optimal number of ambulance locations by maximising the demand coverage. Second, separate location-allocation for the peak and off-peaks, using K-means clustering, was applied to systematically optimise the ambulance positioning in small clusters near demand points. These approaches could substantially improve the existing emergency response time. Distributing ambulances near demand points yielded greater improvements in response time than when the ambulances are stationed near hospitals.     

Monitoring as a partially observable decision problem

Monitoring is an important and costly activity in resource management problems such as containing invasive species, protecting endangered species, preventing soil erosion, and regulating contracts for environmental services. Recent studies have viewed optimal monitoring as a Partially Observable Markov Decision Process (POMDP), which provides a framework for sequential decision making under stochastic resource dynamics and uncertainty about the resource state. We present an overview of the POMDP framework and its applications to resource monitoring. We discuss the concept of the information content provided by monitoring systems and illustrate how information content affects optimal monitoring strategies. Finally, we demonstrate how the timing of monitoring in relation to resource treatment and transition can have substantial effects on optimal monitoring strategies.     

Does risk sharing increase with risk aversion and risk when commitment is limited?

I consider a risk-sharing game with limited commitment, and study how the discount factor above which perfect risk sharing is self-enforcing in the long run depends on agents׳ risk aversion and the riskiness of their endowment. When agents face no aggregate risk, a mean-preserving spread may destroy the sustainability of perfect risk sharing if each agent׳s endowment may take more than three values. With aggregate risk the same can happen with only two possible endowment realizations. With respect to risk aversion the intuitive comparative statics result holds without aggregate risk, but it holds only under strong assumptions in the presence of aggregate risk. In simple settings with two endowment values I also show that the threshold discount factor co-moves with popular measures of risk sharing.