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Allowing for Zeros in Dichotomous-Choice Contingent-Valuation Models

允许零支付意愿的二元选择条件估值模型

Dichotomous-choice contingent-valuation data are modeled using a mixture distribution. The standard parametric survival model is modified such that respondents in the lowest willingness-to-pay category may have either zero willingness to pay or a small positive willingness to pay. In comparison to the standard model, the mixture model leads to a dramatic reduction in estimates of mean willingness to pay. Covariates such as income are found to be more significant in…

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Estimating and Interpreting Models With Endogenous Treatment Effects

内生处理效应模型的估计与解释

This article examines the relationship between two alternative approaches, instrumental variables and control function procedures, for estimating the impact of endogenous treatment effects. Although it is well known that the two approaches generate comparable estimates, the relationship between the estimators and their accompanying endogeneity tests appears not to be well understood. We show that the two procedures are closely related. We also examine the implications of the…

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Bayesian Analysis of an Unobserved-Component Time Series Model of GDP With Markov-Switching and Time-Varying Growths

含马尔可夫转换与时变增长的GDP不可观测成分模型:贝叶斯分析

We propose an unobserved-component time series model of gross domestic product that includes Markov switching as an unobserved component. In addition to a trend component, the model has two time-varying drift components. One drift represents the expected rate of growth during recession; the other drift represents the expected rate during expansion. Estimates indicate a substantial decline in the latter annual rate for the United States from 6.4% in 1950 to 3.6% by 1990. We…

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Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate

定性响应时间序列的条件异方差:银行最优惠贷款利率的吉布斯抽样分析

Previous time series applications of qualitative response models have ignored features of the data, such as conditional heteroscedasticity, that are routinely addressed in time series econometrics of financial data. This article addresses this issue by adding Markov-switching heteroscedasticity to a dynamic ordered probit model of discrete changes in the bank prime lending rate and estimating via the Gibbs sampler. The dynamic ordered probit model of Eichengreen, Watson, and…

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Inferring the Distribution of Households' Duration of Residence From Data on Current Residence Time

从当前居住时长推断家庭总居住时长的分布

Estimates of households' expected duration of residence are important to private and public decisionmakers. The common methods of estimation have been shown to be unreliable. This article presents a measurement framework for estimating total time of residence using five large sets of published government census data on the housing market. By developing a moving-behavior model, the distribution of total residence duration can be estimated from the census data on the age of…

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Bayesian Arbitrage Threshold Analysis

贝叶斯套利阈值分析

A Bayesian estimation procedure is developed for estimating multiple-regime (multiple-threshold) error-correction models appropriate for deviations from financial arbitrage relationships. This approach has clear advantages over classical stepwise threshold autoregressive analysis. Unlike many other applications of threshold models, the knowledge of some costs involved in setting up arbitrage positions allows us to specify an informative prior. To illustrate the Bayesian…

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Structural Stability Testing in Models Estimated by Generalized Method of Moments

广义矩估计模型中的结构稳定性检验

This article proposes a new methodology for testing structural stability in models estimated via generalized method of moments. Like most previous studies of this general problem, attention is focused on the case in which some aspect of the model potentially changes at a single point in the sample, known as the “breakpoint.” Unlike this earlier work, however, our approach is based on a decomposition of the null hypothesis into two components involving parameter constancy and…

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Dynamic Asymmetries in U.S. Unemployment

美国失业率的动态非对称性

The authors examine dynamic asymmetries in U.S. unemployment using nonlinear time series models and Bayesian methods. They find strong statistical evidence in favor of a two-regime threshold autoregressive model. Empirical results indicate that, once parameter and model uncertainty are both taken into account, there are economically interesting asymmetries in the unemployment rate. One finding of particular interest is that shocks that lower the unemployment rate tend to…

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A Generalized Additive Model for Discrete-Choice Data

离散选择数据的广义可加模型

The usual assumption of a linear-in-parameters utility function in a multinomial logit model is relaxed by a sum of one-dimensional nonparametric functions of the explanatory variables. The model generalizes the logistic regression of the generalized additive model for a binary response to a qualitative variable that can assume more than two values. Simulation studies show that the proposed method can recover underlying nonlinearity in utility of various shapes. The model is…

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Time Series Evidence of Unemployment Flows: The Sample Period Matters

失业流动的时间序列证据:样本时期的重要性

Worker flows to and from unemployment occur at all stages of the U.S. business cycle. The flows' dynamics affect the dynamics of the unemployment rate. This article studies the dynamics of unemployment flows and the unemployment rate and explores and documents changes over time. Rigorous diagnostic tests are used to investigate the structural stability of projectional relationships involving flows and the unemployment rate.

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Can Supply and Demand Parameters Be Recovered From Data Generated by Market Institutions?

能否从市场制度生成的数据中恢复供给与需求参数?

The relative accuracy of estimators in recovering supply and demand parameters can depend on the market institutions that generate the data. The parameters of known supply and demand functions are estimated with data from laboratory market experiments with human buyers and sellers. Single-equation estimators dominate simultaneous-equations estimators in recovering supply and demand parameters from posted-offer market data. The inaccuracy of simultaneous-equations estimators…

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Random-Time Aggregation in Partial Adjustment Models

部分调整模型中的随机时间聚合

How is econometric analysis (of partial adjustment models) affected by the fact that, although data collection is done at regular, fixed intervals of time, economic decisions are made at random intervals of time? This article addresses this question by modeling the economic decision-making process as a general point process. Under random-time aggregation, (1) inference on the speed of adjustment is biased-adjustments are a function of the intensity of the point process and…

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Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function

双重异方差随机前沿成本函数的估计

This article extends the results obtained by S. B. Caudill, J. M. Ford, and D. M. Gropper (1995) in estimating and testing stochastic frontier cost functions in the presence of heteroskedastic inefficiency using cross-section data. It suggests the estimation of the model under the assumption of heteroskedasticity in both random terms. This avoids any possible misspecification bias and the use of incorrect tests. The same data as used by Caudill, Ford, and Gropper supports…

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Semiparametric Approaches to Stochastic Panel Frontiers With Applications in the Banking Industry

随机面板前沿的半参数方法及其银行业应用

This article introduces new modeling and estimation methods designed to help mitigate problems of endogeneity and misspecification. The authors use an output distance function to model the technology of a multioutput firm. They also use results from B. U. Park and L. Simar (1995) and B. U. Park, R. C. Sickles, and L. Simar (1998) on semiparametric efficient estimation of panel models to estimate multioutput stochastic distance frontiers for which the distribution of the…

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Predicting U.S. Business-Cycle Regimes

美国商业周期状态的预测

This article examines the use of logistic classification methods for the identification and prediction of postwar U.S. business-cycle expansion and contraction regimes as defined by the National Bureau of Economic Research (NBER) reference turning-point dates. We present a coherent theoretical framework for this task using measures of discriminatory information. The analysis encompasses model selection, parameter estimation, and classification decision rules. We examine the…

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Using Scanner Data to Construct CP1 Basic Component Indexes

利用扫描数据构建消费者价格指数的基本组成指数

This article considers how scanner data could be used in constructing component indexes for the U.S. Consumer Price Index. One product, coffee, in two cities generates over 1.8 million observations in just over two years, so coping with the sheer volume of data would be a challenge. Some other findings are (1) some aggregation of prices into “unit-value” averages is necessary for practical reasons and to avoid bias, (2) chained Laspeyres indexes are very high, (3) “modified”…

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An Asymmetry Generator for Error-Coorection Mechanisms, With Application to Bank Mortgage-Rate Dynamics

误差修正机制的非对称生成器及其在银行抵押贷款利率动态中的应用

Empirical evidence supports asymmetries in the adjustment of prices, interest rates, and other economic variables. The asymmetry hypothesis, however, is often procedurally difficult to set up and test. This article shows that a wide variety of such mechanisms can be nested within an asymmetry generator, which represents the interactions between the disequilibrium term of an error-correction mechanism and an ancillary driver process. The asymmetry hypothesis can then be…

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Preference Heterogeneity and the Rank of Demand Systems

偏好异质性与需求系统的秩

This article examines the effect of preference heterogeneity on nonparametric and parametric tests of the rank of demand systems. Using samples of households drawn from the U.K. Family Expenditure Survey, the authors find that preference heterogeneity increases the rank of demand systems. When the effects of household characteristics on demand are removed by semiparametric techniques, a rank-three demand system appears to be an adequate empirical specification for all…

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Lagged Regression Residuals and Serial-Correlation Tests

滞后回归残差与序列相关检验

A new family of statistics is proposed to test for the presence of serial correlation in linear regression models. The tests are based on partial sums of lagged cross-products of regression residuals that define a class of interesting Gaussian processes. These processes are characterized in terms of regressor functions, the serial-correlation structure, the distribution of the noise process, and the order of the lag of the cross-products of residuals. It is shown that these…

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Testing for a Valid Normalization of Cointegrating Vectors in Vector Autoregressive Processes

向量自回归过程中协整向量有效归一化的检验

This article develops test procedures for checking the validity of general normalizing restrictions imposed on cointegrating vectors in vector autoregressive processes. Such test procedures are of importance because normalizing restrictions, possibly combined with overidentifying restrictions, are often necessary for a proper interpretation of cointegrating vectors. The null hypothesis of the authors' tests assumes that the employed normalization is valid or, alternatively,…

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The Effect of Errors in the CPI on Social Security Finances

消费者价格指数误差对社会保障财务的影响

This article provides detailed estimates of the effects of measurement bias in the Consumer Price Index (CPI) on the Social Security trust funds. Not including the effect of the housing error in the CPI, the estimated overpayment of benefits in 1997 was $26 billion, and, taking interest into account, the total drain on the Old-Age, Survivor and Disability Insurance (OASDI) Trust Funds was $55 billion. At the end of 1997, the present value of the entire effect of the error…

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An Asymmetry Generator for Error-Correction Mechanisms, with Application to Bank Mortgage-Rate Dynamics

误差修正机制的非对称性生成器及银行按揭利率动态应用

Empirical evidence supports asymmetries in the adjustment of prices, interest rates, and other economic variables. The asymmetry hypothesis, however, is often procedurally difficult to set up and test. This article shows that a wide variety of such mechanisms can be nested within an asymmetry generator, which represents the interactions between the disequilibrium term of an error-correction mechanism and an ancillary driver process. The asymmetry hypothesis can then be…

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Using Scanner Data to Construct CPI Basic Component Indexes

利用扫描数据构建 CPI 基本分项指数

This article considers how scanner data could be used in constructing component indexes for the U.S. Consumer Price Index. One product, coffee, in two cities generates over 1.8 million observations in just over two years, so coping with the sheer volume of data would be a challenge. Some other findings are (1) some aggregation of prices into 'unit-value' averages is necessary for practical reasons and to avoid bias, (2) chained Laspeyres indexes are very high, (3) 'modified'…

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Modified Stationarity Tests With Data-Dependent Model-Selection Rules

采用数据依赖模型选择规则的修正平稳性检验

We describe some simple methods for improving the performance of stationarity tests (i.e., tests that have a stationary null and a unit-root alternative). Specifically, we increase the rate of convergence of the test under the unit-root alternative from O p(T) to O p (T 2), then suggest an optimal method of selecting the order of the autoregressive component in the fitted autoregressive integrated moving average model on which the test is based. Simulation evidence suggests…

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