Efficient Estimation of Agricultural Time Series Models with Nonnormal Dependent Variables

Ramírez, Octavio A.; Misra, Sukant K.; Nelson, Jeannie

doi:10.1111/1467-8276.00505

Cited by 25 publications

(16 citation statements)

References 15 publications

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“…), OLS yields the most efficient unbiased estimators for the model's coefficients, i.e. no other technique can produce unbiased slope parameter estimators with lower standard errors (Ramírez, et al [80]). The co-integration methodology is also employed to determine the long run relationships among the variables.…”

Section: Estimation Techniquesmentioning

confidence: 99%

Analysis of Foreign Direct Investment, Agricultural Sector and Economic Growth in Tanzania

Epaphra¹,

Mwakalasya²

2017

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This paper analyzes the effect of foreign direct investment (FDI) on agricultural sector in Tanzania. The paper also examines the declining contribution of agriculture to real GDP growth despite the fact that the sector employs more than 70 percent of the total labour force. Annual time series data spanning from 1990 to 2015 are used to test the significance of the relationship between FDI inflow and agriculture value added-to-GDP ratio on one hand and FDI inflows and economic growth on the other hand. Also, the relationship between agriculture value added and economic growth rate is empirically examined. Variables such as gross fixed capital formation, inflation rate, trade liberalization, real exchange rate and population are considered as control variables. For the purpose of inference, the paper employs classical linear regression model. Ordinary least squares methods are used for estimation. The diagnostic tests including RESET regression errors specification test, Breusch-Godfrey serial correlation LM test, Jacque-Bera-normality test and white heteroskedasticity test reveal that the models have no signs of misspecification and that, the residuals are serially uncorrelated, normally distributed and homoskedastic. Interestingly, empirical results suggest that there is no significant effect of FDI inflows on agriculture value added-to-GDP ratio in Tanzania despite the fact that FDI inflows in economy have been outstanding particularly in past two decades. Unsurprisingly, the results show that FDI inflows-to-GDP ratio and real GDP growth rate are positively correlated. Notwithstanding, agriculture sector, which constitutes the largest proportion of the total labour force, contributes, on average, less than 30 percent, to total GDP. This suggests that the sector is inefficient and therefore, effort towards attracting more FDI aiming at improving productivity in agriculture sector, which in turn may reduce poverty, is much needed.

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Section: Estimation Techniquesmentioning

confidence: 99%

Analysis of Foreign Direct Investment, Agricultural Sector and Economic Growth in Tanzania

Epaphra¹,

Mwakalasya²

2017

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“…A feature of agricultural crop yields in this region is that they tend to increase through time due to technological change, improvements in seed biotechnology, and better management practices. Thus, before working with yields it is common to detrend the data [15].…”

Section: Data Used For Simulation Calibrationmentioning

confidence: 99%

“…The use of robust estimators has gained some popularity in these applications [15], and thus we adopt them here. Using the trend estimate, the trend yield is obtained …”

Section: Data Used For Simulation Calibrationmentioning

confidence: 99%

Estimation efficiency in the modeling of dependence structures: an application of alternative copulas to insurance rating

et al. 2010

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This study assesses the performance of several alternative methods for modeling dependence between random variables in the context of pricing an agricultural insurance contract with multiple underlying risk exposures. Simulation methods are used to estimate the sampling distribution of the insurance rates generated under alternative methods. The results indicate significant variability in performance across methods, and contribute to the risk analysis and insurance literatures by quantitatively assessing out-of-sample efficiency and bias trade-off among competing methods for modeling dependence in limited data scenarios.

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“…The partially adaptive estimation depends on estimating distributional and regression parameters through a parametric error distribution. Partially adaptive estimators (PAEs) are maximum-likelihood (ML) estimators based on the assumed flexible families of error distributions, in the hope that the assumed family is flexible enough to accommodate the shape of the true unknown distribution of the error [39]. These estimators are asymptotically efficient, only if the true error term distribution belongs to the family of the assumed distribution [10,39,49].…”

Section: Introductionmentioning

confidence: 99%

“…Partially adaptive estimators (PAEs) are maximum-likelihood (ML) estimators based on the assumed flexible families of error distributions, in the hope that the assumed family is flexible enough to accommodate the shape of the true unknown distribution of the error [39]. These estimators are asymptotically efficient, only if the true error term distribution belongs to the family of the assumed distribution [10,39,49]. For this reason, it is clear that the assumed family of distribution should be selected so as to nest a wide variety of distributions, as well as represent a broad range of skewness and kurtosis.…”

Section: Introductionmentioning

confidence: 99%

A Monte Carlo simulation study on partially adaptive estimators of linear regression models

Kantar

Usta

Acıtaş

2010

Journal of Applied Statistics

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This paper presents a comprehensive comparison of well-known partially adaptive estimators (PAEs) in terms of efficiency in estimating regression parameters. The aim is to identify the best estimators of regression parameters when error terms follow from normal, Laplace, Student's t , normal mixture, lognormal and gamma distribution via the Monte Carlo simulation. In the results of the simulation, efficient PAEs are determined in the case of symmetric leptokurtic and skewed leptokurtic regression error data. Additionally, these estimators are also compared in terms of regression applications. Regarding these applications, using certain standard error estimators, it is shown that PAEs can reduce the standard error of the slope parameter estimate relative to ordinary least squares.

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Efficient Estimation of Agricultural Time Series Models with Nonnormal Dependent Variables

Cited by 25 publications

References 15 publications

Analysis of Foreign Direct Investment, Agricultural Sector and Economic Growth in Tanzania

Analysis of Foreign Direct Investment, Agricultural Sector and Economic Growth in Tanzania

Estimation efficiency in the modeling of dependence structures: an application of alternative copulas to insurance rating

A Monte Carlo simulation study on partially adaptive estimators of linear regression models

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