Working Papers Series

Papers below are in pdf.

Shawn Ni

WP 11-15
Pension-Induced Rigidities in the Labor Market for School Leaders
Cory Koedel, Jason A. Grissom, Shawn Ni & Michael Podgursky

Educators in public schools in the United States are typically enrolled in defined-benefit pension plans, which penalize across-plan mobility. We use administrative data from Missouri to examine how the mobility penalties affect the labor market for school leaders. We show that pension borders greatly affect leadership flows across schools – for two groups of schools separated by a pension border, our estimates indicate that removing the border will increase leadership mobility between them by 97 to 163 percent. We consider the implications of the pension-induced rigidities in the leadership labor market for schools near pension borders in Missouri. Our findings are of general interest given that thousands of public schools operate near pension boundaries nationwide.

JEL Codes: H5, I2, J3
Keywords: Educator pensions, backloaded compensation, principal quality, leadership quality, compensation in education

WP 11-11
Teacher Pension Incentives and the Timing of Retirement
Shawn Ni and Michael Podgursky

The rising costs and large unfunded liabilities of defined benefit (DB) teacher retirement systems raise questions about their efficacy and viability. Reform of teacher pension plans depends critically on reliable predictions of behavioral responses to alternative pension rules. We estimate an option-value model of individual teacher retirement using administrative data for Missouri teachers. The model fits the observed aggregate retirement behavior very well. We use the estimated structural parameters to simulate retirement behavior under alternative pension rules. Our simulations show that on net the enhancements of Missouri teacher pension benefits in the 1990's lowered the average retirement age for teachers. Conversion from the current DB plan to a defined contribution (DC) plan would have the opposite effect, and would dampen "spikes" in teacher retirement timing. The 1990's enhancements raised welfare for all teachers, however, the DC plan that we simulate has a mixed welfare impact, raising welfare for teachers near retirement but reducing it for teachers with less experience.

JEL Codes: H30, I22, J26, J38
Keywords: teacher pensions, school staffing, school finance.

WP 10-15
Estimating Estate-Specific Price-to-Rent Ratios in Shanghai and Shenzhen: A Bayesian Approach
Jie Chen and Shawn Ni

The price-to-rent ratio, a common yardstick for the value of housing, is difficult to estimate when rental properties are poor substitutes of owner-occupied homes. In this study we estimate price-to-rent ratios of residential properties in two major cities in China, where urban high-rises (estates) comprise both rental and owner-occupied units. We conduct Bayesian inference on estate-specific parameters, using information of rental units to elicit priors of the unobserved rents of units sold in the same estate. We find that the price-to-rent ratios tend to be higher for low-end properties. We discuss economic explanations for the phenomenon and the policy implications.

JEL Codes: C11, R21, R31, G00
Keywords: Housing price, rents, heterogeneity, Bayesian analysis

WP 10-12
Long-Term Oil Price Forecasts: A New Perspective on Oil and the Macroeconomy
J. Isaac Miller and Shawn Ni

We examine how future real GDP growth relates to changes in the forecasted long-term average of discounted real oil prices and to changes in unanticipated fluctuations of real oil prices around the forecasts. Forecasts are conducted using a state-space oil market model, in which global real economic activity and real oil prices share a common stochastic trend. Changes in unanticipated fluctuations and changes in the forecasted long-term average of discounted real oil prices sum to real oil price changes. We find that these two components have distinctly different relationships with future real GDP growth. Positive and negative changes in the unanticipated fluctuations of real oil prices correlate with asymmetric responses of future real GDP growth. In comparison, changes in the forecasted long-term average are smaller in magnitude but are more influential on real GDP. Persistent upward revisions of forecasts in the 2000s had a substantial negative impact on real GDP growth, according to our estimates.

JEL Codes: E31, E32, Q43
Keywords: oil price and the macroeconomy, oil market fundamental, oil price forecasts, Kalman filter

Forthcoming in Macroeconomic Dynamics

WP 09-11
Selection of Multivariate Stochastic Volatility Models via Bayesian Stochastic Search
Antonello Loddo, Shawn Ni & Dongchu Sun

We propose a Bayesian stochastic search approach to selecting restrictions on multivariate regression models where the errors exhibit deterministic or stochastic conditional volatilities. We develop a Markov Chain Monte Carlo (MCMC) algorithm that generates posterior restrictions on the regression coefficients and Cholesky decompositions of the covariance matrix of the errors. Numerical simulations with artificially generated data show that the proposed method is effective in selecting the data-generating model restrictions and improving the forecasting performance of the model. Applying the method to daily foreign exchange rate data, we conduct stochastic search on a VAR model with stochastic conditional volatilities.

JEL Codes: C11, C15, C32
Keywords: Bayesian VAR, Particle Filter, Markov Chain Monte Carlo, Model Selection

WP 07-14
Excess Sensitivity in Consumption without Liquidity Constraint: Evidence from Monthly Household Panel Data
Shawn Ni & Youn Seol

The monthly salaries and allowances of Korean government employees are known in advance but vary greatly throughout the year. Using a large Korean monthly panel data set from 1994 to 2003, we examine how nondurable consumption expenditure in households headed by government employees responds to predictable income changes. We find excess sensitivity in consumption during the pre-Asian financial crisis era in households headed by young government employees with low liquid assets or low income. These household features are commonly associated with liquidity constraints. Further analysis shows that despite the apparent association, liquidity constraint is not the most convincing explanation for the excess sensitivity. Instead, the empirical finding is consistent with the theory that certain households deviate from consumption smoothing when the effort involved exceeds the welfare gained.

JEL Codes: D12, E21
Keywords: household consumption, excess sensitivityhousehold consumption, excess sensitivity

WP 07-09
Heterogeneous Information and Investment under Uncertainty
Shawn Ni & Ronald A. Ratti

A sudden change in investment environment shifts objective uncertainty (characterized by parameters that determine the distribution of returns) and at the same time heightens subjective uncertainty (about the data generating parameters) unevenly across investors. For a given state of economy, the uncertainty facing the investor is the sum of the uncertainty in the data and the uncertainty of the investor?s assessment of the expected return distribution. In this model the option value of waiting to invest depends not only on the objective uncertainty as in the traditional theory but varies systematically with investor information and Bayesian updating of outlook for the project. Simulation of the model suggests that during a state characterized by greater uncertainty and higher potential expected return investment will be by an abnormally high percentage of informed investors and may increase overall. For over 10,000 instances of firm-level FDI data for Korea from 1996 to 2001, regression results are consistent with the hypothesis that disproportionably more FDI is made by experienced (hence more informed) investors during heightened uncertainty.

JEL Codes: D8, E22, F21
Keywords: uncertainty, investor information, option value, Bayesian updating, FDI

WP 05-03
High Corruption Income in Ming and Qing China
Shawn Ni and Pham Hoang Van

We develop an economic model that explains historical data on government corruption in Ming and Qing China. In our model, officials’ extensive powers result in corrupt income matching land’s share in output. We estimate corrupt income to be between 14 to 22 times official income resulting in about 22% of agricultural output accruing to 0.4% of the population. The results suggest that eliminating corruption through salary reform was possible in early Ming but impossible by mid-Qing rule. Land reform may also be ineffective because officials could extract the same rents regardless of ownership. High officials’ incomes and the resulting inequality may have also created distortions and barriers to change that could have contributed to China’s stagnation over the five centuries 1400-1900s.

JEL Codes: O10, O53
Keywords: Corruption, China
Published in Journal of Development Economics 2006

WP 02-18
Corruption, Distortion, and Stagnation in Ming and Qing China
Shawn Ni and Pham Hoang Van

We model corruption in Ming and Qing China and calibrate the model to the Qing economy. In our model, officials’ extensive powers result in corrupt income matching land’s share in output. Whereas a previous accounting from Qing records estimated corruption income at 18.5 times salary, our model estimates the ratio to be 20.9. Our model shows 18.7% of agricultural output accrued to 0.4% of the population compared to 16.9% from the historical record. The results suggest (1) eliminating corruption through salary reform was possible in early Ming but impossible by mid-Qing rule; (2) land reform was ineffective because officials could extract the same rents regardless of ownership; (3) high officials’ incomes and the resulting inequality created distortions and barriers to change that may explain China’s stagnation.

*Updated Manuscript

WP 02-12
Bayesian Estimator of Vector-Autoregressive Model Under the Entropy Loss
Shawn Ni and Dongchu Sun

The present study makes two contributions to the Bayesian Vector-Autoregression (VAR) literature. The first contribution is derivation of the Bayesian VAR estimator under the intrinsic entropy loss. The Bayesian estimator, which is distinctly different from the posterior mean, involves the frequentist expectation of a function of VAR variables. We find that the condition that allows for a closed-form expression of the frequentist expectation is violated even when the VAR is stationary, making it difficult to compute the Bayesian estimates via standard Markov Chain Monte Carlo (MCMC) procedures. The second contribution of the paper concerns MCMC simulation of the Bayesian estimator without using the closed-form expression of the frequentist expectation. A novelty of our MCMC algorithms is that they jointly simulate the posteriors of frequentist moments of VAR variables as well as the posteriors of VAR parameters. Numerical simulations show that the algorithms are surprisingly efficient.

published with revisions (with D. Sun and X. Sun) in Journal of Business and Economic Statistics 2007

WP 02-11
Alternative Bayesian Estimators for Vector-Autoregressive Models
Shawn Ni and Dongchu Sun

This paper compares frequentist risks of several Bayesian estimators of the VAR lag parameters and covariance matrix under alternative priors. With the constant prior on the VAR lag parameters, the asymmetric LINEX estimator for the lag parameters does better overall than the posterior mean. The posterior mean of covariance matrix performs well in most cases. The choice of prior has more significant effects on the estimates than the form of estimators. The shrinkage prior on the VAR lag parameters dominates the constant prior, while Yang and Berger’s reference prior on the covariance matrix dominates the Jeffreys prior. Estimation of a VAR using the U.S. macroeconomic data reveals significant differences between estimates under the shrinkage and constant priors.

Published in Journal of Business and Economic Statistics, vol 23, no 1, January 2005 pp 105-117.

WP 02-10
Noninformative Priors and Frequentist Risks of Bayesian Estimators of Vector-Autoregressive Models
Shawn Ni and Dongchu Sun

In this study, we examine posterior properties and frequentist risks of Bayesian estimators based on several non-informative priors in Vector Autoregressive (VAR) models. We prove existence of the posterior distributions and posterior moments under a general class of priors. Using a variety of priors in this class we conduct numerical simulations of posteriors. We find that in most examples Bayesian estimators with a shrinkage prior on the VAR coefficients and the reference prior of Yang and Berger (1994) on the VAR covariance matrix dominate MLE, Bayesian estimators with the diffuse prior, and Bayesian estimators with the prior used in RATS. We also examine the informative Minnesota prior and find that its performance depends on the nature of the data sample and on the tightness of the Minnesota prior. A tightly set Minnesota prior is better when the data generating processes are similar to random walks, but the shrinkage prior or constant prior can be better otherwise.

published with revisions in Journal of Econometrics 2003.

WP 00-10
Price Uncertainty and Consumer Welfare in an Intertemporal Setting
Shawn Ni and Neil Raymon

In this paper we examine how increases in intertemporal price uncertainty affect the welfare of a consumer. In the preference structure of the consumer the coefficient of relative risk aversion and the elasticity of intertemporal substitution (EIS) are parametrically independent. We find that under empirically plausible circumstances, for each given degree of risk aversion an increase in price uncertainty reduces consumer welfare if the EIS is lower than a corresponding threshold value. Overall our results suggest that for parameter estimates found in much of the empirical literature, increases in intertemporal price uncertainty are likely to reduce consumer welfare.

published in Journal of Economic Dynamics and Control, July 2004, vol 28, pp 1877-1901.