Browsing by Author "Brown, Bryan W."

Now showing 1 - 7 of 7
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    A time series analysis of the Japanese yen
    (1988) Kwon, Jae-Jung; Brown, Bryan W.
    This paper sought to address the question as to whether the exchange rate can be forecasted more accurately by a monetary model of exchange rate determination or the random walk in the case of the Japan-U.S. exchange rate. The evidence of Meese and Rogoff (1983) on the out-of-sample forecasting performance of structural exchange rate models in comparison to the random walk model portrays a disappointing picture of structural models. I re-considered the issue for the Japanese yen for a more recent period. Besides out-of-sample evidence, within-sample evidence was also examined. The recent work of Phillips and Perron was employed so as to verify that the exchange rate series is well approximated by a random walk model without drift but with time dependent heteroscedasticity. Having established this benchmark, structural monetary models are constructed to see whether one can obtain better within-sample and/or out-of-sample results. It appeared that the random walk can be beaten.
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    Equilibrium, efficient-markets, and liquidity in the cash-in-advance model
    (1991) Arroyo, Cristino Rodriguez, III; Brown, Bryan W.
    The existence of equilibrium is a test of the internal consistency of an economic model. In any model with domestic moneys and dividend-yielding assets, the first question is: will money be dominated by assets in equilibrium? In cash-in-advance models domestic moneys always have positive liquidity value as instruments for domestic commodity transactions. If a non-dominated liquidity role for domestic currencies is posited existence of equilibrium is not usually problematic. For the case where information flows lead to binding cash-in-advance constraints an equilibrium exists in which domestic moneys have positive liquidity value. This equilibrium possesses the unit velocity property, but leads to a sharper characterization of equilibrium market and shadow prices in relation to fundamentals. That fiat money should be the unique provider of liquidity services is not necessary for equilibrium. It is possible to construct models with well-defined equilibria in which financial assets provide liquidity services. In these models the pricing equations for liquidity-providing assets contain premia for these services over and above risk premia and returns for delaying consumption. Such models can also generate new relationships between the velocity of money or the spot exchange rate and asset returns. That markets be information-efficient is, however, necessary for equilibrium. Consequently, any rejection of efficient-markets is evidence against the assumptions of the equilibrium theory. Consider, for instance, the case of the efficiency of forward exchange rates vis-a-vis spot rates. Depending on whether forward speculation is consummated through arbitrage of currencies or of assets (e.g., covered and uncovered bonds) the forward efficiency condition will or will not involve liquidity premia. In testing forward efficiency in both models we find, however, there is no material change in the results. Forward efficiency appears to be robust as well to specifications of the utility function. However there is evidence that forward efficiency is not robust to either the measurement of consumption risk, or the choice of covariance estimator of the forecast error.
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    Essays in semiparametric and nonparametric estimation with application to growth accounting
    (2001) Jeon, Byung Mok; Brown, Bryan W.
    This dissertation develops efficient semiparametric estimation of parameters and expectations in dynamic nonlinear systems and analyzes the role of environmental factors in productivity growth accounting. The first essay considers the estimation of a general class of dynamic nonlinear systems. The semiparametric efficiency bound and efficient score are established for the problems. Using an M-estimator based on the efficient score, the feasible form of the semiparametric efficient estimators is worked out for several explicit assumptions regarding the degree of dependence between the predetermined variables and the disturbances of the model. Using this result, the second essay develops semiparametric estimation of the expectation of known functions of observable variables and unknown parameters in the class of dynamic nonlinear models. The semiparametric efficiency bound for this problem is established and an estimator that achieves the bound is worked out for two explicit assumptions. For the assumption of independence, the residual-based predictors proposed by Brown and Mariano (1989) are shown to be semiparametric efficient. Under unconditional mean zero assumption, I proposed an improved heteroskedastic autocorrelation consistent estimator. The third essay explores the directional distance function method to analyze productivity growth. The method explicitly evaluates the role of undesirable outputs of the economy, such as carbon dioxide and other green-house gases, have on the frontier production process which we specify as a piecewise linear and convex boundary function. We decompose productivity growth into efficiency change (catching up) and technology change (innovation). We test the statistical significance of the estimates using recently developed bootstrap method. We also explore implications for growth of total factor productivity in the OECD and Asia economies.
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    Essays on parametric and nonparametric modeling and estimation with applications to energy economics
    (1999) Gao, Weiyu; Brown, Bryan W.; Sickles, Robin
    My dissertation research is composed of two parts: a theoretical part on semiparametric efficient estimation and an applied part in energy economics under different dynamic settings. The essays are related in terms of their applications as well as the way in which models are constructed and estimated. In the first essay, efficient estimation of the partially linear model is studied. We work out the efficient score functions and efficiency bounds under four stochastic restrictions---independence, conditional symmetry, conditional zero mean, and partially conditional zero mean. A feasible efficient estimation method for the linear part of the model is developed based on the efficient score. A battery of specification test that allows for choosing between the alternative assumptions is provided. A Monte Carlo simulation is also conducted. The second essay presents a dynamic optimization model for a stylized oilfield resembling the largest developed light oil field in Saudi Arabia, Ghawar. We use data from different sources to estimate the oil production cost function and the revenue function. We pay particular attention to the dynamic aspect of the oil production by employing petroleum-engineering software to simulate the interaction between control variables and reservoir state variables. Optimal solutions are studied under different scenarios to account for the possible changes in the exogenous variables and the uncertainty about the forecasts. The third essay examines the effect of oil price volatility on the level of innovation displayed by the U.S. economy. A measure of innovation is calculated by decomposing an output-based Malmquist index. We also construct a nonparametric measure for oil price volatility. Technical change and oil price volatility are then placed in a VAR system with oil price and a variable indicative of monetary policy. The system is estimated and analyzed for significant relationships. We find that oil price volatility displays a significant negative effect on innovation. A key point of this analysis lies in the fact that we impose no functional forms for technologies and the methods employed keep technical assumptions to a minimum.
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    Heteroskedasticity and serial correlation in tests for rational expectations and/or simple market efficiency: A white-type approach
    (1989) Ligeralde, Antonio Velasco; Brown, Bryan W.
    The simple market efficiency hypothesis implies that prediction errors, such as forward less spot exchange rates, will be orthogonal to elements of the information set. One can therefore test for market efficiency via ordinary least squares by regressing the prediction errors on pieces of information available at the time the predictions are made and checking if the intercept term and slope coefficients are jointly equal to zero. Two econometric complications have to be dealt with when testing for market efficiency in the above manner. The first complication arises from the fact that multi-period-ahead predictions lead to an inter-temporal band structure for the covariance matrix. This complication can be handled by employing Hansen's Generalized Method of Moments (GMM) estimate which takes explicit account of the band structure of the covariance matrix. The second complication arises from the fact that the disturbances in the regression may also be heteroskedastic. Insofar as heteroskedasticity might adversely affect inference, we propose a White-type test that indicates whether or not a covariance matrix correction for heteroskedasticity is necessary. The test essentially checks if the difference between the homoskedastic and heteroskedastic consistent forms of Hansen's GMM estimate tend towards zero. Monte Carlo experiments examining the performance of the proposed test show that at least in large samples, the White-type test works well under a variety of heteroskedastic specifications. By actually applying the above procedures to test the simple foreign exchange market efficiency hypothesis, we find that for particular regression specifications and data sets, it does not make a practical difference whether we base inferences on the homoskedastic or the heteroskedastic consistent forms of Hansen's GMM covariance estimate. For other data sets and regression specifications, however, we are able to reject market efficiency only if we use the appropriate form of Hansen's GMM estimate as determined by the White-type test.
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    Semi- and non-parametric estimation and testing of economic models
    (1995) Ming, Xing; Brown, Bryan W.
    Chapter one provides a new estimator for the ordered polychotomous model. The estimator is based on the use of the average of the standard normal densities with different means as a parametric approximation to the density of the error term. The method also, for the first time, provides a consistent, differentiable estimator of the distribution function of the error term. Chapter two employs the conventional interpretation of endogeneity in econometric models to develop a way of eliminating the inconsistency resulting from endogenous explanators in cross sectional models. The method first obtains an estimate of the unobserved heterogeneity responsible for the endogeneity and then creates a synthetic observation by taking a non-parametric weighted average of nearby observations. The deviations are produced from these synthetic means thereby eliminating the unobserved heterogeneity. The procedure is particularly useful for estimating models when the endogenous regressors are censored or appear non-linearly in the primary equation. Chapter three first calculates the exact distribution of Blum et al's (1961) statistic, which is based on a comparison of the sample joint CDF with the product of the sample marginal CDF's, for very small sample size and simulate the distribution quantiles of it for sample size not large enough to employ the asymptotic result. Secondly, the asymptotic distribution of the statistic constructed from residuals and/or predicted values, to test the independence of the error term and the regressors in nonlinear regression models, is obtained. Thirdly, bootstrap technique is used to obtain the distribution quantiles of the statistic constructed from residuals and/or predicted values. The test is nonparametric in that it does not specify the parametric form of distributions of the error term and the regressors.
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    The economics of undocumented immigration: Mexican participation in the U.S. labor market
    (1988) Olea, Hector Alonso; Brown, Bryan W.
    This study addresses the impact of Mexican illegal immigration on the U.S. labor market. It constitutes a first step towards developing rigorous structural econometric models that empirically analyze undocumented labor force dynamics. Structural estimation of the labor supply and the participation decision of illegal Mexican immigration requires the solution of intricate theoretical problems that have not been addressed in previous literature. The analysis developed here identifies those problems and proposes innovative solutions. In particular, undocumented participation in the U.S. labor market is studied in the context of life cycle theory and stochastic behavior. The empirical part of the analysis reviews the problems of sample selection and missing observations that characterize the available data on Mexican migration. The proposed empirical specification is evaluated employing limited dependent variables procedures, where a Tobit simultaneous equation model is solved using maximum likelihood methods. According to the empirical results, Mexican undocumented immigration may be viewed as a transitory phenomenon. Individuals switch back and forth between Mexico and the U.S. reacting not only to income differentials, but also to social, family and economic attachments in their home-communities. Mexican workers seem to have little incentives to invest in human capital specific to the U.S., such as the ability to speak English. This behavior may be result of the partial transferability of Mexican skills, i.e. formal education, to the secondary market in the United States. Finally, contrary to conventional wisdom, the empirical evidence suggests that exogenous increases in U.S. wages, i.e. a non-expected hike in the legal minimum wage, may actually discourage Mexican undocumented participation in the U.S. labor market.