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In this paper, we investigate the nature of rational expectations equilibria for economic epidemiological models, with a particular focus on the behavioral origins and dynamics of epidemiological bifurcations. Unlike mathematical epidemiological models, economic epidemiological models can produce regions of indeterminacy or instability around the endemic steady states due to endogenous human responses to epidemiological circumstance variation, medical technology change, or health policy reform. We consider SI, SIS, SIR and SIRS versions of economic compartmental models and show how well-intentioned public policy may contribute to disease instability, uncertainty, and welfare losses.

Trading volume changes based on market microstructure will impact asset prices, which will lead to transaction price changes. Based on the extended Hasbrouck–Foster–Viswanathan (HFV) model, we study the statistical characteristics of daily permanent price impact and daily temporary price impact using high-frequency data from Chinese Stock Markets. We estimate this model using tick-by-tick data for 16 selected stocks that are traded on the Shanghai Stock Exchange. We find the following: (1) the time series of both the permanent price impact and temporary price impact exist in stationarity and long-term memory; (2) there is a strong correlation between the permanent price impact among assets, while the correlation coefficient of the temporary price impact is generally weak; (3) the time interval has no significant influence on the trade volume and the price change at the tick frequency, which means that it is not necessary to take into account the time interval between adjacent transaction in high-frequency trading; and (4) the bid-ask spread is an effective factor to explain trading price change, but has no significant impact on trade volume.

This paper studies the option valuation problem of non-Gaussian and asymmetric GARCH models from a state-space structure perspective. Assuming innovations following an infinitely divisible distribution, we apply different estimation methods including filtering and learning approaches. We then investigate the performance in pricing S&P 500 index short-term options after obtaining a proper change of measure. We find that the sequential Bayesian learning approach (SBLA) significantly and robustly decreases the option pricing errors. Our theoretical and empirical findings also suggest that, when stock returns are non-Gaussian distributed, their innovations under the risk-neutral measure may present more non-normality, exhibit higher volatility, and have a stronger leverage effect than under the physical measure.

We derive risk-neutral probability densities for future euro/Swiss franc exchange rates as implied by option prices. We find that the credibility of the Swiss franc floor decreased somewhat as the spot exchange rate approached the lower bound of 1.20 CHF per euro. We also compare the forecasting performance of a random walk benchmark model with an error-correction model (ECM) augmented with option-implied break probabilities of breaching the currency floor. We find some evidence that the augmented ECM has an informational advantage over the random walk when using one-month break probabilities. But we find that one-month option-implied densities cannot predict the entire range of exchange rate realizations.

Log-linear models are popular in practice because the slope of a log-transformed regressor is believed to give an unit-free elasticity. This widely held belief is, however, not true if the model error term has a heteroskedasticity function that depends on the regressor. This paper examines various mean – and quantile-based elasticities ( mean of elasticity, elasticity of conditional mean, quantile of elasticity, and elasticity of conditional quantile ) to show under what conditions these are equal to the slope of a log-transformed regressor. A particular attention is given to the ‘elasticity of conditional mean (i.e., regression function)’, which is what most researchers have in mind when they use log-linear models, and we provide practical ways to find it in the presence of heteroskedasticity. We also examine elasticities in exponential models which are closely related to log-linear models. An empirical illustration for health expenditure elasticity with respect to income is provided to demonstrate our main findings.

This paper empirically investigates the dynamics between budget deficit and government debt in the U.S. using two different measures of the budget deficit: the current budget deficit and cyclically-adjusted budget deficit. A threshold Vector autoregression (VAR) model is estimated to explore the dynamics in different regimes using quarterly data from 1947:Q1 to 2017:Q3. The specification test rejects a linear VAR model against the threshold VAR. When we use the current budget deficit, regime 1 resemble governments prioritize minimizing budget deficit and debt, whereas, regime 2 resemble otherwise. When we use the cyclically adjusted budget deficit, regime 1 resemble economic expansions, whereas, regime 2 resemble recessions. The impulse responses show evidence of asymmetry and counter-cyclicality. The impulse responses also indicate that an increase in the debt dictate the government’s response towards minimizing the budget deficit and tend to prioritize budget deficit less when the economy expands.