creator: Ng, Serena
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Parametric and non-parametric approaches to price and tax reform
description- – In many public policy problems, we need to estimate the way in which policy changes affect people's behavior. In the analysis of tax and subsidy reform, which is the topic of this paper, we need to know how tax-induced price changes affect the amounts that people buy of the taxed goods. We present various economic and statistical approaches to obtaining the estimates that are required. We consider the structural methods that are standard in economics, where the behavior and welfare of individual agents are simultaneously captured by the specification of utility functions whose parameters are to be estimated. We argue that these methods are less useful than alternatives that directly consider the derivatives of the regression function of average behavior. We consider both parametric and nonparametric estimators of these derivatives in the context of price reform for foods in Pakistan, focussing on the advantages and disadvantages of"average derivative estimation"(ADE) as proposed by Hardle and Stoker (1989) and Stoker (1991). Average derivative estimation is attractive in principle because it directly estimates the statistics that are required for policy analysis. In the practical case considered here, neither technique is a clear winner; each has strengths and weaknesses.
- – WP376
- – 1997-12-01
- – application/pdf
Explaining the Persistence of Commodity Prices
description- – This paper extends the Competitive Storage Model by incorporating prominent features of the production process and financial markets. A major limitation of this basic model is that it cannot successfully explain the degree of serial correlation observed in actual data. The proposed extensions build on the observation that in order to generate a high degree of price persistence, a model must incorporate features such that agents are willing to hold stocks more often than predicted by the basic model. We therefore allow unique characteristics of the production and trading mechanisms to provide the required incentives. Specifically, the proposed models introduce (i) gestation lags in production with heteroskedastic supply shocks, (ii) multiperiod forward contracts, and (iii) a convenience return to inventory holding. The rational expectations solutions for twelve commodities are numerically solved. Simulations are then employed to assess the effects of the above extensions on the time series properties of commodity prices. Results indicate that each of the features above partially account for the persistence and occasional spikes observed in actual data. Evidence is presented that the precautionary demand for stocks might play a substantial role in the dynamics of commodity prices.
- – WP374
- – 1997-12-01
- – application/pdf
A Semi-Parametric Factor Model of Interest Rates and Tests of the Affine Term Structure
description- – Many continuous time term structure of interest rate models assume a factor structure where the drift and volatility functions are affine functions of the state variable process. These models involve very specific parametric choices of factors and functional specifications of the drift and volatility. Moreover, under the affine term structure restrictions not all factors necessarily affect interest rates at all maturities simultaneously. This class of so called affine models covers a wide variety of existing empirical as well as theoretical models in the literature. In this paper we take a very agnostic approach to the specification of these diffusion functions and test implications of the affine term structure restrictions. We do not test a specific model among the class of affine models per se. Instead, the affine term structure restrictions we test are based on the derivatives of the responses of interest rates to the factors. We also test how many and which factors affect a particular rate. These tests are conducted within a framework which models interest rates as functions of"fundamental"factors, and the responses of interest rates to these factors are estimated with non-parametric methods. We consider two sets of factors, one based on key macroeconomic variables, and one based on interest rate spreads. In general, despite their common use we find that the empirical evidence does not support the restrictions imposed by affine models. Besides testing the affine structure restrictions we also uncover a set of fundamental factors which appear remarkably robust in explaining interest rate dynamics at the long and short maturities we consider.
- – WP403
- – 1997-09-01
- – application/pdf
Accounting for Trends in the Almost Ideal Demand System
description- – Flexible functional forms of indirect utility and expenditure functions are frequently used in approximating the behavior of utility maximizing consumers to arrive at demand systems that can be easily estimated. A common finding in time series estimations of the Almost Ideal Demand System is strong persistence in the estimated residuals. This paper suggests two explanations for this result. First, the functions used to approximate total expenditure does not allow for the possibility of economic growth. Hence when the data on expenditure have trends, the inadequacy of the approximation results in residuals that are serially correlated. Second, when the economy grows and/or prices trend at different rates, Stone's price index provides a poor approximation to the theoretically appropriate price variable. The consequence is also reflected in the error term. Simulations are used to illustrate these arguments and cointegration is proposed as a guide to model specification.
- – WP368
- – 1997-06-01
- – application/pdf
Testing for ARCH in the Presence of a Possibly Misspecified Conditional Mean
description- – Ever since the development of the Autoregressive Conditional Heteroskedasticity (ARCH) model (Engle [1982]), testing for the presence of ARCH has become a routine diagnostic. One popular method of testing for ARCH is T times the R^2 from a regression of squared residuals on p of its lags. This test has been shown to have a Lagrange multiplier interpretation and is asymptotically distributed as a Chi^2(p) random variable. Underlying this test is the assumption of a correctly specified conditional mean. In this paper, we consider the properties of the ARCH test when there is a possibly misspecified conditional mean. Examples of misspecification include omitted variables, structural change, and parameter instability. We show that misspecification will lead to overrejection of the null of conditional homoskedasticity. We demonstrate the use of recursive residuals to improve the fit of a first stage conditional mean regression. We illustrate these results via Monte Carlo simulation and consider two empirical examples.
- – WP370
- – 1998-08-27
- – application/pdf
How Important are Intergenerational Transfers of Time? A Macroeconomic Analysis
description- – This paper examines the implications of intergenerational transfers of time and money for labor supply and capital accumulation. Although intergenerational transfers of time in the form of grandparenting are as substantial as monetary transfers in the data, little is known about the role and importance of time transfers. In this paper, we calibrate an overlapping generations model extended to allow for both time and monetary transfers to the US economy. We use simulations to show that time transfers have important positive effects on capital accumulation and that these effects can be as significant as those of monetary transfers. However, while time transfers increase the labor supply of the young, monetary transfers produce an income effect that tends to decrease work effort. We also find that child care tax credits have little impact on parental time and money transfers, but that a universal child tax credit would increase the welfare of the rich while the poor would benefit from a means-tested program.
- – WP395
- – 1998-07-01
- – application/pdf
Estimating the Rational Expectations Model of Speculative Storage: A Monte Carlo Comparison of Three Simulation Estimators
description- – The non-negativity constraint on inventories imposed on the rational expectations theory of speculative storage implies that the conditional mean and variance of commodity prices are nonlinear in lagged prices and have a kink at a threshold point. In this paper, the structural parameters of this model are estimated using three simulation based estimators. The finite sample properties of the Simulated Methods of Moments estimator of Duffie and Singleton (1993), the Indirect Inference estimator of Gourieroux, Monfort and Renault (1993), and the matching score estimator of Gallant and Tauchen (1996) are assessed. Exploiting the invariant distribution implied by the theory allows us to assess the error induced by simulations. Our results show that while all three estimators produce reasonably good estimates with properties that stack up well with those of the PMLE, there are tradeoffs among the three estimators in terms of bias, efficiency, and computation demands. Some estimators are more sensitive to the sample size and the number of simulations than others. A careful choice of the moments/auxiliary models can lead to a substantial reduction in bias and an improvement in efficiency. Increasing the number of simulated data points can sometimes reduce the bias and improve the efficiency of the estimates when the sample size is small.
- – WP373
- – 1999-04-01
- – application/pdf
Determining the Number of Factors in Approximate Factor Models
description- – In this paper we develop some econometric theory for factor models of large dimensions. The focus is the determination of the number of factors, which is an unresolved issue in the rapidly growing literature on multifactor models. We propose some panel C(p) criteria and show that the number of factors can be consistently estimated using the criteria. The theory is developed under the framework of large cross-sections (N) and large time dimensions (T). No restriction is imposed on the relation between N and T. Simulations show that the proposed criteria yield almost precise estimates of the number of factors for configurations of the panel data encountered in practice.
- – WP440
- – 2000-12-01
- – application/pdf
Intergenerational Linkages in Consumption Behavior
description- – Consumption is partly a social activity, yet most studies of consumer behavior treat households in isolation. We investigate familial relationships in consumption patterns using a sample of parents and their children from the Panel Study of Income Dynamics. We find a positive and statistically significant parent-specific effect on childrenês consumption even after controlling for the effect of parental income, and we find similar effects for sibling pairs. Child consumption responds negatively to large post-retirement shortfalls in consumption of the parents. This behavior holds up even after allowing for the possibility of smaller parent-to-child transfers made necessary by the parental consumption shortfalls. These results suggest that although income is an important source of the intergenerational correlation, parental choices and experiences also affect consumption behavior of the children.
- – WP482
- – 2000-11-08
- – application/pdf
A PANIC Attack on Unit Roots and Cointegration
description- – This paper develops a new methodology that makes use of the factor structure of large dimensional panels to understand the nature of non-stationarity in the data. We refer to it as PANICÜ a 'Panel Analysis of Non-stationarity in Idiosyncratic and Common components'. PANIC consists of univariate and panel tests with a number of novel features. It can detect whether the nonstationarity is pervasive, or variable-specific, or both. It tests the components of the data instead of the observed series. Inference is therefore more accurate when the components have different orders of integration. PANIC also permits the construction of valid panel tests even when cross-section correlation invalidates pooling of statistics constructed using the observed data. The key to PANIC is consistent estimation of the components even when the regressions are individually spurious. We provide a rigorous theory for estimation and inference. In Monte Carlo simulations, the tests have very good size and power. PANIC is applied to a panel of inflation series.
- – WP519
- – 2001-12-01
- – application/pdf
A New Look at Panel Testing of Stationarity and the PPP Hypothesis
description- – This paper uses a decomposition of the data into common and idiosyncratic components to develop procedures that test if these components satisfy the null hypothesis of stationarity. The decomposition also allows us to construct pooled tests that satisfy the cross-section independence assumption. In simulations, tests on the components separately generally have better properties than testing the observed series. However, the results are less than satisfactory, especially in comparison with similar procedures developed for unit root tests. The problem can be traced to the properties of the stationarity test, and is not due to the weakness of the common-idiosyncratic decomposition. We apply both panel stationarity and unit root tests to real exchange rates. We found evidence in support of a large stationary common factor. Rejections of PPP are likely due to non-stationarity of country-specific variations.
- – WP518
- – 2001-10-01
- – application/pdf
A Note on the Selection of Time Series Models
description- – We consider issues related to the order of an autoregression selected using information criteria. We study the sensitivity of the estimated order to i) whether the effective number of observations is held fixed when estimating models of different order, ii) whether the estimate of the variance is adjusted for degrees of freedom, and iii) how the penalty for overfitting is defined in relation to the total sample size. Simulations show that the lag length selected by both the Akaike and the Schwarz information criteria are sensitive to these parameters in finite samples. The methods that give the most precise estimates are those that hold the effective sample size fixed across models to be compared. Theoretical considerations reveal that this is indeed necessary for valid model comparisons. Guides to robust model selection are provided.
- – WP500
- – 2001-06-15
- – application/pdf
Tests for Skewness, Kurtosis, and Normality for Time Series Data
description- – We present the sampling distributions for the coefficient of skewness, kurtosis, and a joint test of normality for time series observations. In contrast to independent and identically distributed data, the limiting distributions of the statistics are shown to depend on the long run rather than the short-run variance of relevant sample moments. Monte Carlo simulations show that the test statistics for symmetry and normality have good finite sample size and power. However, size distortions render testing for kurtosis almost meaningless except for distributions with thin tails such as the normal distribution. Nevertheless, this general weakness of testing for kurtosis is of little consequence for testing normality. Combining skewness and kurtosis as in Bera and Jarque (1981) is still a useful test of normality provided the limiting variance accounts for the serial correlation in the data.
- – WP501
- – 2001-06-01
- – application/pdf
Demand Systems With Nonstationary Prices
description- – Relative prices are nonstationary and standard root-T inference is invalid for demand systems. But demand systems are nonlinear functions of relative prices, and standard methods for dealing with nonstationarity in linear models cannot be used. Demand system residuals are also frequently found to be highly persistent, further complicating estimation and inference. We propose a variant of the Translog demand system, the NTLOG, and an associated estimator that can be applied in the presence of nonstationary prices with possibly nonstationary errors. The errors in the NTLOG can be interpreted as random utility parameters. The estimates have classical root-T limiting distributions. We also propose an explanation for the observed nonstationarity of aggregate demand errors, based on aggregation of consumers with heterogeneous preferences in a slowly changing population. Estimates using US data are provided.
- – WP441
- – 2004-11-01
- – application/pdf
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