Moment-based estimation of smooth transition regression models with endogenous variables

Nonlinear regression models have been widely used in practice for a variety of time series and cross-section datasets. For purposes of analyzing univariate and multivariate time series data, in particular, smooth transition regression (STR) models have been shown to be very useful for representing and capturing asymmetric behavior. Most STR models have been applied to univariate processes, and have made a variety of assumptions, including stationary or cointegrated processes, uncorrelated, homoskedastic or conditionally heteroskedastic errors, and weakly exogenous regressors. Under the assumption of exogeneity, the standard method of estimation is nonlinear least squares. The primary purpose of this paper is to relax the assumption of weakly exogenous regressors and to discuss moment-based methods for estimating STR models. The paper analyzes the properties of the STR model with endogenous variables by providing a diagnostic test of linearity of the underlying process under endogeneity, developing an estimation procedure and a misspecification test for the STR model, presenting the results of Monte Carlo simulations to show the usefulness of the model and estimation method, and providing an empirical application for inflation rate targeting in Brazil. We show that STR models with endogenous variables can be specified and estimated by a straightforward application of existing results in the literature.     

Reopening the convergence debate: A new look at cross-country growth empirics

There are two sources of inconsistency in existing cross-country empirical work on growth: correlated individual effects and endogenous explanatory variables. We estimate a variety of cross-country growth regressions using a generalized method of moments estimator that eliminates both problems. In one application, we find that per capita incomes converge to their steady-state levels at a rate of approximately 10 percent per year. This result stands in sharp contrast to the current consensus, which places the convergence rate at 2 percent. We discuss the theoretical implications of this finding. In another application, we perform a test of the Solow model. Again, contrary to prior reults, we reject both the standard and the augmented version of the model.     

Effects of EU dairy policy reform for Dutch dairy farming: a primal approach using GMM estimation

This paper estimates a production function for milk using ageneralised method of moments estimator to avoid the endogeneityproblem. Using the first-order conditions for profit maximisation,the economic effects for individual Dutch dairy farms of the2003 EU dairy policy reform are analysed. With an expected milkprice decrease of 21 per cent, profit decreases on average by22 per cent. EU direct payments compensate for roughly 53 percent of this fall in profit. The profit reduction means that69 per cent of all small farms have negative income from farming,compared with 15 per cent in the initial situation.     

关于后验矩的近似计算

文章介绍了数理统计中实数或向量参数的正函数的后验平均、方差和预测密度的近似计算。     

Instrumental variable estimation based on grouped data

The paper considers the estimation of the coefficients of a single equation in the presence of dummy intruments. We derive pseudo ML and GMM estimators based on moment restrictions induced either by the structural form or by the reduced form of the model. The performance of the estimators is evaluated for the non-Gaussian case. We allow for heteroscedasticity. The asymptotic distributions are based on parameter sequences where the number of instruments increases at the same rate as the sample size. Relaxing the usual Gaussian assumption is shown to affect the normal asymptotic distributions. As a result also recently suggested new specification tests for the validity of instruments depend on Gaussianity. Monte Carlo simulations confirm the accuracy of the asymptotic approach.     

A TEST OF A GENERAL EQUILIBRIUM STOCK OPTION PRICING MODEL

An empirical version of the Cox, Ingersoll, and Ross (1985a) call option pricing model is derived, assuming execution price uncertainty in the options market. the pricing restrictions come in the form of moment conditions in the option pricing error. These can be estimated and tested using a version of the method of simulated moments (MSM). Simulation estimates, obtained by discretely approximating the risk-neutral processes of the underlying stock price and the interest rate, are substituted for analytically unknown call prices. the asymptotics and other aspects of the MSM estimator are discussed. the model is tested on transaction prices at 15-minute intervals. It substantially outperforms the Black-Scholes model. the empirical success of the Cox-Ingersoll-Ross model implies that the continuous-time interest rate implicit in synchronous transaction quotes of 90-day Treasury-bill futures contracts is an-albeit noisy-proxy for the instantaneous volatility on common stock. the process of the instantaneous volatility is found to be close to nonstationary. It is well approximated by a heteroskedastic unit-root process. With this approximation, the Cox-Ingersoll-Ross model only slightly overprices long-maturity options.     

Regression with errors in variables: estimators based on third order moments

In this paper consistent and, in a well–defined sense, optimal moment–estimators of the regression coefficient in a simple regression model with errors in variables are derived. The asymptotic variance and other asymptotic properties of these estimators are given. As is known for a long time, serious estimation problems exist in this model. There are two ways out of this problem: using either additional assumptions or additional information in the data. A lot of attention has been paid to the use of additional assumptions. However, quite often this leads to rather unrealistic models. In this paper we use additional information in the data. That means here that, besides first and second order moments, third order moments are formulated as functions of the model parameters. Besides theoretical derivations a small study with generated data is discussed. This study shows that for samples larger than 50 the estimates we consider behave nicely.     

TESTING FOR STATIONARITY WITH A BREAK IN PANELS WHERE THE TIME DIMENSION IS FINITE

In this paper, we consider the case of finite time dimension in the panel stationarity tests with structural breaks. By fixing T, the finite sample properties of the tests for both micro (T small and N large) and macro (both T and N large) panel data are generally greatly improved. More importantly, the derivation of the tests for finite T and , as opposed to joint asymptotic where N and simultaneously, avoids the imposition of the rate condition making the test valid for any (T, N) blend. Four models corresponding to the usual combination of breaks are considered. The asymptotic distributions of the test are derived under the null hypothesis and are shown to be normally distributed. Their moments for T fixed are derived analytically employing Ghazal’s corollary 1. The case with unknown breaks is also considered. The proposed tests have generally empirical sizes that are very close to the nominal size. The Monte Carlo simulations show that the power of the test statistics increases substantially with N and T.     

Impact of foreign direct investment on greenhouse gas emissions in agriculture of developing countries

This research analyses the impact of foreign direct investment on greenhouse gas emissions in the agriculture sector of developing countries. Panel data from 63 developing countries for the period 2005 to 2014 was used to estimate a dynamic econometric model by applying a system‐generalised method of moments. The empirical results indicate a positive impact of foreign direct investment in agriculture on the carbon dioxide equivalent emission intensity in developing countries. The results provide weak support for the pollution havens hypothesis and imply the importance of coordination between foreign direct investment and environmental policies.     

Then and Now: Examining Older People's Engagement in Outdoor Recreation Across the Life Course

Outdoor recreation provides a range of health and wellbeing benefits and facilitates engagement with natural environments. We explore older people's participation in outdoor recreation throughout their lives to examine how past experiences shape engagement later in life. A qualitative life history approach, consisting of semi-structured interviews and a focus group in three place-specific (urban, rural, and small town coastal) case studies in Scotland, was adopted. Thematic analysis revealed ways in which childhood experiences shaped adult engagement and highlighted life course transitions where behaviour change was most pronounced. Place and gender were considered as factors which may affect responses. Participants identified the points of getting married, becoming a parent, children entering adolescence, retirement, the onset of disabilities or ill health, and the death of others as “moments of change” in the extent and/or form of their outdoor recreation. The findings highlight potential for targeted interventions to promote outdoor recreation throughout life.