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.     

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.     

Modelling the implied volatility surface based on Shanghai 50ETF options

We develop a dynamic factor model to forecast the implied volatility surface (IVS) of Shanghai Stock Exchange 50ETF options. Based on the assumption that dynamic change in IVS is mean-reverting and Markovian, we use a state space model to capture the dynamics of IVS, and set the latent factors to be the Ornstein–Uhlenbeck processes. We obtain the optimal estimations of parameters using the Kalman filter algorithm. Empirical results show that our model performs better than the traditional IVS model in terms of fitting ability and prediction performance.     

Sovereign default risk in OECD countries: Do global factors matter?

We study the determinants of sovereign default risk for a group of 23 OECD countries using quarterly data spanning the period between 2000:Q1 and 2016:Q3. Applying the recently developed panel dynamic heterogeneous common correlated effects estimator of Chudik and Pesaran (2015) our study innovates in considering potential endogeneity issues and cross-sectional dependence. We control for both global risk appetite and monetary policy stance, as well as country risk ratings. The results show that common factors are the main drivers of solvency risk for our set of countries. Specially relevant, we find that macroeconomic determinants are not significant predictors of long-term sovereign spreads.     

Exploring the role of knowledge management practices on exports: A dynamic capabilities view

Drawing on dynamic capabilities view, this work provides empirical evidence on the role of knowledge management practices on export intensity in SMEs in a mature and global, non-high-tech industry. A quantitative study with structural equation modeling was carried out on a sample of 157 Spanish and Italian manufacturing companies in the ceramic tile industry. Our results suggest the existence of a mediating effect of dynamic capabilities on exports, hence the implementation of knowledge management practices is a necessary but not sufficient condition to improve exporting, requiring the existence of dynamic capabilities to reconfigure these capabilities. Findings highlight the relevance of knowledge practices to foster exports, providing new insights for managers dealing with dynamic capabilities in SMEs.     

The effects of oil price shocks on inflation in the G7 countries

This study examines the effects of three types of oil price shocks on inflation in the G7 countries with a new method of isolating oil price shocks. Based on monthly data from January 1997 to January 2019, we find that each oil price shock has the largest effect on U.S. inflation among the G7 countries and each country’s response to oil price shocks is different. Moreover, a rolling-window analysis shows that supply shocks, demand shocks and risk shocks have dynamic effects on inflation. The effect of supply shocks on inflation is strong before the financial crisis, but weakens during the crisis. However, the effect of demand shocks increases sharply in this time. The effect of risk shocks mainly occurs during the financial crisis and the European debt crisis. In addition, this study uses two ways to verify the robustness of the results. Our empirical results have important implications for policymakers and manufacturers, since the results provide a good explanation for the response of inflation in the G7 countries to the oil price shocks from different sources.     

The synergistic effect of insurance and banking sector activities on economic growth in Africa

It is widely understood that the insurance and banking sectors of every economy perform some functions in driving economic growth. What is not yet well documented is whether their roles are complimentary or substitutive. With the aid of the dynamic panel generalized method of moments (GMM) estimation technique, this paper evaluates the synergistic effect of both sectors on economic growth in a panel of 10 African countries that are responsible for most of the activities in the continent’s financial sector. The insurance-banking-growth nexus was also examined through bootstrap panel causality tests. The results show that the life insurance market and the banking sector, as well as the non-life insurance market and the banking sector, are complimentary. We find that, overall, the relationship between the insurance and banking sectors in Africa is a complimentary one and that their synergistic impact on economic growth is positive. The feedback hypothesis was also confirmed in the relationship between the insurance sector and economic growth and between the banking sector and economic growth.     

A comparison of programming languages in macroeconomics

We solve the stochastic neoclassical growth model, the workhorse of modern macroeconomics, using C++14, Fortran 2008, Java, Julia, Python, Matlab, Mathematica, and R. We implement the same algorithm, value function iteration, in each of the languages. We report the execution times of the codes in a Mac and in a Windows computer and briefly comment on the strengths and weaknesses of each language.