HETEROGENEOUS EFFECTS OF THE ACA MEDICAID EXPANSION ON HOSPITAL FINANCIAL OUTCOMES

This study examines the effect of the Affordable Care Act's Medicaid expansion on hospital financial outcomes. A key innovation relative to prior studies is that we explicitly account for heterogeneity across states in the timing and extent of the expansion as well as across hospital types. We find that Medicaid expansion led to a decrease in uncompensated care expenditures and an increase in average operating margins. The effects were larger in states where the Medicaid expansion led to a greater increase in program eligibility. Operating margins improved most for public hospitals and facilities located in rural areas. (JEL I11, I13, I18)     

Real business cycles: is neglecting demand shocks justified?

Real business cycle models generally neglect demand shocks. Technological productivity shocks are the primary source of economic fluctuations. The multisectoral consequences of this assumption are described in the well-known model of Long and Plosser (1983). The presented paper shows that according to their view consumer goods sectors must be found in lagging positions. However, generalizing the strong assumption of pure supply driven dynamics by some demand-determined influences leads to ambiguous theoretical results such that only empirical evidence can answer the question whether sectoral lead-lag relationships are in accordance with real business cycle theory. Using cross spectral analysis and causality tests leads to a rejection of the Long and Plosser view of intersectoral comovements. On the contrary, the empirical results suggest that the backward propagation mechanism of demand shocks dominates the forward propagation of supply disturbances.     

Second thoughts on free riding

We use the strategy method to classify subjects into cooperator types in a large-scale online Public Goods Game and find that free riders spend more time on making their decisions than conditional cooperators and other cooperator types. This result is robust to reversing the framing of the game and is not driven by cognitive ability, confusion, or natural swiftness in responding. Our results suggest that conditional cooperation serves as a norm and that free riders need time to resolve a moral dilemma.     

Sources of Fluctuations in the Real Exchange Rates and Trade Balances of the G‐7: A Sign Restriction VAR Approach

This paper estimates structural vector autoregression models of output, the real exchange rate and trade balance for the group of seven leading advanced economies (G‐7). Unlike previous studies, we do not impose long‐run purchasing power parity as an identifying assumption; instead, the shocks underlying the model are structurally identified using a set of theory‐consistent sign restrictions. Empirical results show that nominal shocks account for most of the long‐run variability in trade balances across the G‐7 countries. We are able to attribute this finding to long‐run movements in the real exchange rate, as the real exchange rate is significantly affected by nominal shocks in the long run.     

Cattle as a consistently resilient agricultural commodity

This study compares a range of agricultural commodities over periods of varying economic circumstances. These commodities are examined over three categories, including returns, risk, and contribution to portfolio optimisation. Consistency in these categories is determined over four equal three-year stages which comprise pre-GFC (Global Financial Crisis), GFC, post-GFC and post-post GFC. To demonstrate resilience in the most extreme circumstances, the study uses Conditional Value at Risk (CVaR), which measures extreme risk in the tail of a distribution, as the risk measure and risk-return optimiser. The study thus provides a unique and comprehensive extreme-risk based focus which identifies and ranks the consistency of performance of agricultural commodities over a range of criteria and conditions. Cattle commodities consistently demonstrate the strongest overall performance in the categories examined.     

Generalized spatial autocorrelation in a panel-probit model with an application to exporting in China

This paper proposes a generalized spatial panel-data probit model with spatial autocorrelation of the dependent variable, the time-invariant individual shocks, and the remainder disturbances. It proposes its estimation with a Bayesian Markov chain Monte Carlo procedure. Simulation results show that the proposed estimation method performs well in small- to medium-sized samples. This method is then applied to the analysis of export-market participation of 1451 Chinese firms between 2002 and 2006 in the prefecture-level city of Wenzhou in the province of Zhejiang. Empirical results show that two of the three forms of the hypothesized spatial autocorrelation are significant, namely the spatial lag for the dependent variable and the time-invariant firm-specific shocks, but not the time-variant shocks. Ignoring any of these significant spatial effects would lead to misspecification.