Regime-Switching Stochastic Volatility and Short-Term Interest Rates.

In this paper, we introduce regime-switching in a two-factor stochastic volatility model to explain the behavior of short-term interest rates. The regime-switching stochastic volatility (RSV) process for interest rates is able to capture all possible exogenous shocks that could be either discrete, as occurring from possible changes in the underlying regime, or continuous in the form of `market-news' events. We estimate the model using a Gibbs Sampling based Markov Chain Monte Carlo algorithm that is robust to complex nonlinearities in the likelihood function. We compare the performance of our RSV model with the performance of other GARCH and stochastic volatility two-factor models. We evaluate all models with several in-sample and out-of-sample measures. Overall, our results show a superior performance of the RSV two-factor model.Short-term interest rates, stochastic volatility, regime switching, MCMC methods.

Oil price shocks and U.S. economic activity: an international perspective

Oil price shocks are thought to have played a prominent role in U.S. economic activity. In this paper, we employ Bayesian methods with a dynamic stochastic general equilibrium model of world economic activity to identify the various sources of oil price shocks and economic fluctuation and to assess their effects on U.S. economic activity. We find that changes in oil prices are best understood as endogenous. Oil price shocks in the 1970s and early 1980s and the 2000s reflect differing mixes of shifts in oil supply and demand, and differing sources of oil price shocks have differing effects on economic activity. We also find that U.S. output fluctuations owe mostly to domestic shocks, with productivity shocks contributing to weakness in the 1970s and 1980s and strength in the 2000s.Petroleum products - Prices ; Petroleum industry and trade ; Economic conditions - United States ; Business cycles

Demand Estimation at Manufacturer-Retailer Duo: A Macro-Micro Approach

This dissertation is divided into two phases. The main objective of this phase is to use Bayesian MCMC technique, to attain (1) estimates, (2) predictions and (3) posterior probability of sales greater than certain amount for sampled regions and any random region selected from the population or sample. These regions are served by a single product manufacturer who is considered to be similar to newsvendor. The optimal estimates, predictions and posterior probabilities are obtained in presence of advertising expenditure set by the manufacturer, past historical sales data that contains both censored and exact observations and finally stochastic regional effects that cannot be quantified but are believed to strongly influence future demand. Knowledge of these optimal values is useful in eliminating stock-out and excess inventory holding situations while increasing the profitability across the entire supply chain. Subsequently, the second phase, examines the impact of Cournot and Stackelberg games in a supply-chain on shelf space allocation and pricing decisions. In particular, we consider two scenarios: (1) two manufacturers competing for shelf space allocation at a single retailer, and (2) two manufacturers competing for shelf space allocation at two competing retailers, whose pricing decisions influence their demand which in turn influences their shelf-space allocation. We obtain the optimal pricing and shelf-space allocation in these two scenarios by optimizing the profit functions for each of the players in the game. Our numerical results indicate that (1) Cournot games to be the most profitable along the whole supply chain whereas Stackelberg games and mixed games turn out to be least profitable, and (2) higher the shelf space elasticity, lower the wholesale price of the product; conversely, lower the retail price of the product, greater the shelf space allocated for that product

Bayesian analysis of DSGE models

This paper reviews Bayesian methods that have been developed in recent years to estimate and evaluate dynamic stochastic general equilibrium (DSGE) models. We consider the estimation of linearized DSGE models, the evaluation of models based on Bayesian model checking, posterior odds comparisons, and comparisons to vector autoregressions, as well as the nonlinear estimation based on a second-order accurate model solution. These methods are applied to data generated from correctly specified and misspecified linearized DSGE models, and a DSGE model that was solved with a second-order perturbation method.Macroeconomics ; Vector autoregression

Oil Price Shocks and U.S. Economic Activity: An International Perspective

Oil price shocks are thought to have played a prominent role in U.S. economic activity. In this paper, we employ Bayesian methods with a dynamic stochastic general equilibrium model of world economic activity to identify the various sources of oil price shocks and economic fluctuation and to assess their effects on U.S. economic activity. We find that changes in oil prices are best understood as endogenous. Oil price shocks in the 1970s and early 1980s and the 2000s reflect differing mixes of shifts in oil supply and demand, and differing sources of oil price shocks have differing effects on economic activity. We also find that U.S. output fluctuations owe mostly to domestic shocks, with productivity shocks contributing to weakness in the 1970s and 1980s and strength in the 2000s.oil price, international business cycles, general equilibrium, Bayesian estimation

Near-optimal protocols in complex nonequilibrium transformations

The development of sophisticated experimental means to control nanoscale systems has motivated efforts to design driving protocols which minimize the energy dissipated to the environment. Computational models are a crucial tool in this practical challenge. We describe a general method for sampling an ensemble of finite-time, nonequilibrium protocols biased towards a low average dissipation. We show that this scheme can be carried out very efficiently in several limiting cases. As an application, we sample the ensemble of low-dissipation protocols that invert the magnetization of a 2D Ising model and explore how the diversity of the protocols varies in response to constraints on the average dissipation. In this example, we find that there is a large set of protocols with average dissipation close to the optimal value, which we argue is a general phenomenon.Comment: 6 pages and 3 figures plus 4 pages and 5 figures of supplemental materia

Cyclical movements in unemployment and informality in developing countries

This paper analyzes the cyclical properties of worker flows in Brazil and Mexico, two important developing countries with large unregulated or “informal” sectors. It generates three stylized facts that are critical to the accurate modeling of the sector and which suggest the need to rethink the approaches to date. First, the unemployment rate is countercyclical essentially because job separations of informal workers increase dramatically in recessions. Second, the share of formal employment is countercyclical because of the difficulty of finding formal jobs from inactivity, unemployment and other informal jobs during recessions rather than because of increased separation from formal jobs. Third, flows from formality into informality are not countercyclical, but, if anything, pro-cyclical. Together, these challenge the conventional wisdom that has guided the modeling the sector that informal workers are primarily those rationed out of the formal labor market. They also offer a new synthesis of the mechanics of the cyclical adjustment process. Finally, the paper offers estimates of the moments of worker flows series that are needed for calibration.Labor Markets,Labor Policies,Population Policies,,Labor Standards

Assessing the Performance of Simple Contracts Empirically: The Case of Percentage Fees

This paper estimates the cost of using simple percentage fees rather than the broker optimal Bayesian mechanism, using data for real estate transactions in Boston in the mid-1990s. This counterfactual analysis shows that interme- diaries using the best percentage fee mechanisms with fees ranging from 5.4% to 7.4% achieve 85% or more of the maximum profit. With the empirically observed 6% fees intermediaries achieve at least 83% of the maximum profit and with an optimally structured linear fee, they achieve 98% or more of the maximum profit