Douglas G. Steigerwald

Asymptotic Bias for Quasi-Maximum-Likelihood Estimators in Conditional Heteroskedasticity Models

For conditional heteroskedasticity models, the authors study the identification condition that is required for consistency of a non-Gaussian quasi-maximum-likelihood estimator. They show that, if the conditional mean is zero or if a symmetry condition is satisfied, then the identification condition is satisfied. Without symmetry, an additional parameter, for the location of the innovation density, must be added for identification. For the conditional variance parameters of a GARCH process, there is no efficiency loss from adding the parameter under symmetry, when the parameter is not needed.

The Underground Economy of Fake Antivirus Software

Fake antivirus (AV) programs have been utilized to defraud millions ofcomputer users into paying as much as one hundred dollars for a phony softwarelicense. As a result, fake AV software has evolved into one of the most lucrativecriminal operations on the Internet. In this paper, we examine the operations of threelarge-scale fake AV businesses, lasting from three months to more than two years.More precisely, we present the results of our analysis on a trove of data obtainedfrom several backend servers that the cybercriminals used to drive their scam operations.Our investigations reveal that these three fake AV businesses had earned acombined revenue of more than

Consumption Adjustment under Time-Varying Income Uncertainty

130 million dollars. A particular focus of our analysisis on the financial and economic aspects of the scam, which involves legitimatecredit card networks as well as more dubious payment processors. In particular, wepresent an economic model that demonstrates that fake AV companies are activelymonitoring the refunds (chargebacks) that customers demand from their credit cardproviders. When the number of chargebacks increases in a short interval, the fakeAV companies react to customer complaints by granting more refunds. This lowersthe rate of chargebacks and ensures that a fake AV company can stay in businessfor a longer period of time. However, this behavior also leads to unusual patternsin chargebacks, which can potentially be leveraged by vigilant payment processorsand credit card companies to identify and ban fraudulent firms.

Testing for absolute purchasing power parity

We study the effect of income uncertainty on consumption in a model that includes precautionary saving. In contrast to previous studies, we focus on time-series variation in income uncertainty. Our time-series measure of income uncertainty is constructed from a panel of forecasts. We find evidence of precautionary saving in that increases in income uncertainty are related to increases in aggregate rates of saving. We also find evidence that anticipated income growth rates have less explanatory power for consumption growth rates after conditioning on income uncertainty. The evidence indicates the presence of forward-looking consumers who gradually adjust precautionary savings in response to changing income uncertainty.

Purchasing power parity, unit roots, and dynamic structure

Abstract Purchasing power parity (PPP) is an equilibrium condition equating the nominal exchange rate between two countries with the relative price of an identical bundle of goods in each country. Previous time-series researchers use price indices to study PPP, so they test relative PPP. We use new data that measures price levels, so we test absolute PPP. Price levels provide a test of absolute PPP because, unlike price indices, price levels do not contain a base period in which the nominal exchange rate equals the price ratio by construction. We find support for absolute PPP.

Adaptive estimation in time series regression models

Recent studies of purchasing power parity (PPP) account for the possible presence of unit roots in nominal exchange rates and relative price indices by applying standard unit-root tests to real exchange rates, which are ratios of nominal exchange rates and relative price indices. These studies occasionally find evidence of PPP, but as a whole, the evidence is not definitive. Standard unit-root tests impose a restrictive dynamic structure between nominal exchange rates and relative price indices. I specify and estimate a generalized dynamic structure. I reject the dynamic restrictions implicit in standard unit-root tests of PPP, and find stronger evidence of PPP than do most other recent studies.

Asymptotic Behavior of a t Test Robust to Cluster Heterogeneity

This work develops adaptive estimators for a linear regression model with serially correlated errors. We show that these results continue to hold when the order of the ARMA process characterizing the errors is unknown. The finite sample results are promising, indicating that substantial efficiency gains may be possible for samples as small as 50 observations. We use these estimators to investigate the behavior of the forward foreign exchange market.

ECONOMETRIC ESTIMATION OF FORESIGHT: TAX POLICY AND INVESTMENT IN THE UNITED STATES

For a cluster-robust t-statistic under cluster heterogeneity we establish that the cluster-robust t-statistic has a gaussian asymptotic null distribution and develop the effective number of clusters, which scales down the actual number of clusters, as a guide to the behavior of the test statistic. The implications for hypothesis testing in applied work are that the number of clusters, rather than the number of observations, should be reported as the sample size, and the effective number of clusters should be reported to guide inference. If the effective number of clusters is large, testing based on critical values from a normal distribution is appropriate.

Noise reduced realized volatility: a kalman filter approach

We develop a method for measuring the foresight agents have. We first dichotomize an agents information at current date t into knowledge up to date t 1 f and expectations after t 1 f. We then form a residual-based test statistic that allows us to compare prediction errors for econometric models based on different values of f. We illustrate the method, examining investment around tax reforms to measure the foresight firms have about tax policy. In this illustration, current investment appears to reflect currently available information but little foresight other than foresight of enacted policy changes.

Markov Regime-Switching Tests: Asymptotic Critical Values

Microstructure noise contaminates high-frequency estimates of asset price volatility. Recent work has determined a preferred sampling frequency under the assumption that the properties of noise are constant. Given the sampling frequency, the high-frequency observations are given equal weight. While convenient, constant weights are not necessarily efficient. We use the Kalman filter to derive more efficient weights, for any given sampling frequency. We demonstrate the efficacy of the procedure through an extensive simulation exercise, showing that our filter compares favorably to more traditional methods.