Purpose: Gross Domestic Product(GDP) depends on Agriculture, Service, and industry performance. The main aim of the study is to assess the relationship between dependent variable GDP and Independent variables agriculture, industry, and service sector by using the n-variable Regression Model at...

In this paper, I present a simple characterization of the sample selection bias problem that is also applicable to the conceptually distinct econometric problems that arise from truncated samples and from models with limited dependent variables. The problem of sample selection bias is fit within...

Two-stage-least-squares (2SLS) estimates are biased towards OLS estimates. This bias grows with the degree of over-identification and can generate highly misleading results. In this paper we propose two simple alternatives to 2SLS and limited-information-maximum-likelihood (LIML) estimators for...

Australian All Ordinaries Stock Index has been in the headline since 1997 for its tear jerking effect on the stock exchange. Present work attempts to develop a realistic time-series model to explain the behavior of the stock price data during 2 January 1997 to 29 December 2006 collected from...

This paper considers the statistical and economic justification for one widely-used method of adjusting data from social experiments to account for dropping-out behavior due to Bloom (1984). We generalize the method to apply to distributions not just means, and present tests of the key...

Different local projection (LP) estimators for structural impulse responses of proxy vector autoregressions are reviewed and compared algebraically and with respect to their small sample suitability for inference. Conditions for numerical equivalence and similarities of some estimators are...

This paper studies the problems of estimation and inference in the linear trend model: yt=à+þt+ut, where ut follows an autoregressive process with largest root þ, and þ is the parameter of interest. We contrast asymptotic results for the cases þþþ 1 and þ=1, and argue that the most...

In empirical regression analysis, the existence of high multicollinearity suggests that predictors may provide redundant information and cause a reduction in statistics power. Meanwhile, dropping correlated variables may result in mis-specified models with biased parameters. Unlike previous...

We present a new method to sample random variables through the use of orthogonal polynomial expansions of the associated quantile function that utilize the inverse transform technique. In particular, we obtain an explicit representation of the quantile function through an orthogonal expansion...

This paper presents an (S,s) model for automobile consumption and estimates it using a data set of US households. The model allows for unobserved heterogeneity in both the target level and the band width, takes into account the possibility of a zero desired level, constrains the band to be non...