Goodness Aye - Academia.edu (original) (raw)

Papers by Goodness Aye

African Journal of Agricultural Research, Nov 4, 2010

In this study, technical efficiency of traditional and improved maize farms as well as impact of ... more In this study, technical efficiency of traditional and improved maize farms as well as impact of technological innovation on technical efficiency were investigated. Two-stage procedure was followed. In the first stage, technical efficiency scores were obtained from four different models namely parametric stochastic distance frontier, parametric stochastic production frontier and two nonparametric distance frontiers and the results were compared. In the second stage, efficiency estimates from each of the four methods were regressed against hybrid seed and other policy variables using Tobit model. A total of 240 farm households were selected for the study using a multistage random sampling technique. The selected households were interviewed using semi-structured questionnaires. Results showed that farmers operated with substantial technical inefficiency irrespective of the approach employed. Technical efficiency estimates obtained from the distance frontier approaches are positively and significantly correlated. In all the models, hybrid seed was found to have positive and significant impact technical efficiency. Other policy variables that had significant impact on technical efficiency include education, extension, credit and land. These results reinforce the need for further investment in agricultural research and development for increased productivity, food security and poverty reduction in Nigeria.

The study evaluates the technical, allocative and cost efficiencies of maize farmers and analyses... more The study evaluates the technical, allocative and cost efficiencies of maize farmers and analyses the impact of technological innovations on these efficiency measures. The investigation of farm efficiency is of vital importance from both microeconomic and macroeconomic points of view. It indicates the potentials there is to improve productivity, household welfare, overall economic growth and poverty reduction by improving efficiency. It also assists policy makers in better targeting and priority setting. Policy conclusions may vary with the approach used for analysis. A number of efficiency studies in Nigeria employed the stochastic production or cost function approach. While the former may suffer from simultaneous equation bias, the later may not be practical when there is limited input price variation among farms as is evidenced in the study area or when there is a systematic deviation from cost minimizing behaviour. This study contributes methodologically by employing a parametri...

Resources Policy, 2021

Oil plays a pivotal role in the growth of agriculture as a combustion lubricant for machineries a... more Oil plays a pivotal role in the growth of agriculture as a combustion lubricant for machineries and equipment used in the farming enterprise. Several studies have shown that a relationship exists between oil prices and agricultural growth without clear boundaries beyond which these prices are detrimental to the growth. Therefore, this study is conducted to identify the threshold above which oil prices will adversely affect agricultural growth in South Africa. Real West Texas Intermediate (WTI) and Real Brent crude oil prices in both Dollars and Rands were used as threshold variables in the threshold regression model of agricultural growth. The findings showed that beyond the threshold values of 12.99%, 15.68%, 15.69% and 15.70%, the prices of Real WTI crude oil in Dollars, Real Brent crude oil in Dollars, Real WTI crude oil in Rands and Real Brent crude oil in Rands respectively will have significant negative effects on agricultural growth in South Africa.

Journal of Human Ecology, 2012

This study estimates the technical, allocative and cost efficiency of farm households using stoch... more This study estimates the technical, allocative and cost efficiency of farm households using stochastic distance and stochastic production frontiers. Further, the study examines determinants of efficiency. Data was collected from a random sample of 240 maize farmers in Benue State Nigeria using structured questionnaires. Results from both distance and production frontiers show that farmers in the area are inefficient. Although the efficiency measures from the two frontiers are quantitatively different from each another, the overall consistency check shows that the farm households were ranked similarly by both approaches. This is particularly robust to allocative and cost efficiency. Improved maize seed, inorganic fertilizers, conservation practices, size of farm holdings, education, and access to extension services, credit and market were found to have significant impact on efficiency. Thus, investment in agricultural research coupled with complementary policies is an effective instrument for revamping agriculture and poverty reduction in Nigeria.

Journal of Housing Research, 2015

Journal of Housing Research, 2013

Tliis paper provides empirical evidence on the long-and short-run relationships between real hous... more Tliis paper provides empirical evidence on the long-and short-run relationships between real house and stock prices of South Africa. Standard linear tests may not detect the existence of these relationships between time series especially in the presence of structural shifts or regime changes, which, in turn, may cause nonlinearities in the observed series. Thus, in this study, both linear and nonparametric cointegration and Granger causality tests were conducted. Results from the linear cointegration test show^ed no long-run relationship between house and stock prices. The linear Granger causality test produced no evidence of causality either. In contrast, the nonparametric cointegration test revealed a long-nm one-to-one relationship between the two series, with the nonparametric Granger causality test indicating a bi-directional causality. Therefore, stability in the housing market drives stability in the equity market and vice versa. ' .

The Journal of Economic Asymmetries, 2018

This paper examines whether proxies of political risk exposure at the firm-level can predict the ... more This paper examines whether proxies of political risk exposure at the firm-level can predict the aggregate stock market volatility. Utilizing a nonparametric causality-in-quantiles test which not only guards against misspecification due to nonlinearity, but also tests for causality over the entire conditional distribution of the realized volatilities, we show that political risk exposure can serve as a strong predictor of bad realized volatility, while the causal effects are non-existent in the case of overall and good realized volatilities. Our findings provide novel insight to the welldocumented asymmetric volatility puzzle and the effect of political uncertainty on stock market fluctuations via the investor attention channel. The results also suggest that political risk exposure could be a contributing factor to jump risk in the cross-section of returns.

Cogent Economics & Finance, 2016

Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch ge... more Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public.

Global Business and Economics Review, 2016

This study applies the panel KSS test with a Fourier function through the Sequential Panel Select... more This study applies the panel KSS test with a Fourier function through the Sequential Panel Selection Method, proposed by Chortareas and Kapetanios (2009), to test whether housing bubbles exist in South Africa using the ratio of housing price to income in 9 provinces (i.e.,

Working Papers, Dec 7, 2012

This study examines the time series behaviour of South African house prices within a fractional i... more This study examines the time series behaviour of South African house prices within a fractional integration modelling framework while identifying potential breaks and outliers. We used quarterly data on the six house price indexes, namely affordable, luxury, middle-segment (all sizes, large, medium and small sizes), covering the periods 1966:Q1-2012:Q1 for the different middle-segments, 1966:Q3-2012:Q1 for the luxury segment and 1969:Q4-2012:Q1 for the affordable segment. In general, there is persistence in South African house prices with breaks identified. Our results show that in the cases of affordable and luxury, shocks will be transitory, disappearing in the long run, while for the remaining four series of the middle-segment, shocks will be permanent. Hence, for the middle-segment series strong policy measures must be adopted in the event of negative shocks, in order to recover the original trends.

Empirica, 2015

This study investigates the predictability of 11 industrialized stock returns with emphasis on th... more This study investigates the predictability of 11 industrialized stock returns with emphasis on the role of U.S. returns. Using monthly data spanning 1980:2 to 2014:12, we show that there exist multiple structural breaks and nonlinearities in the data. Therefore, we employ methods that are capable of accounting for these and at the same time date stamping the periods of causal relationship between the U.S. returns and those of the other countries. First we implement a subsample analysis which relies on the set of models, data set and sample range as in Rapach et al. (2013). Our results show that while the U.S. returns played a strong predictive role based on the OLS pairwise Granger causality predictive regression and news-diffusion models, it played no role based on the pooled version of the OLS model and its role based on the adaptive elastic net model is weak relative to Switzerland. Second, we implement our preferred model: a bootstrap rolling window approach using our newly updated data on stock returns for each countries, and find that U.S. stock return has significant predictive ability for all the countries at certain sub-periods. Given these results, it would be misleading to rely on results based on constant-parameter linear models that assume that the relationship between the U.S. returns and those of other industrialized countries are permanent, since the relationship is, in fact, timevarying, and holds only at specific periods.

Journal of Applied Economics, 2015

This paper examines the causal relationship between economic policy uncertainty (EPU) and equity ... more This paper examines the causal relationship between economic policy uncertainty (EPU) and equity market uncertainty (EMU) in the US using linear and nonlinear Granger causality tests. We use daily data on the newly developed indexes by Baker et al. (2013a) covering 1985:01:01 to 2013:06:14. Results from the linear causality tests indicate strong bidirectional causality. We test for parameters stability, and find strong evidence of short run parameter instability, thus invalidating any conclusion from the full sample linear estimations. Therefore we turn to nonlinear tests. Using Hiemstra and Jones (1994), Diks and Panchenko (2006), and Kyrtsou and Labys (2006) symmetric test, we observe a stronger predictive power from EMU to EPU than from EPU to EMU. Using the

In this paper, we test for the structural stability of both bivariate and multivariate predictive... more In this paper, we test for the structural stability of both bivariate and multivariate predictive regression models for equity premium in South Africa over the period of 1990:01 to 2010:12, based on 23 financial and macroeconomic variables. We employ a wide range of methodologies, namely, the popular Andrews (1993) statistic and the Bai (1997) subsample procedure in conjunction with the Hansen (2000) heteroskedastic fixed-regressor bootstrap. We also used the Elliott and Muller (2003) statistic and Bai and Perron (1998, 2003a, 2004) methodologies. We find strong evidence of at least two structural breaks in 22 of 23 bivariate predictive regression models. We also obtain evidence of structural instability in the multivariate predictive regression models of equity premium. Our results also show that the predictive ability of the 23 variables can vary widely across different regimes.

Cogent Economics & Finance, 2014

Emerging Markets Review, 2015

This study investigates the asymmetric and time-varying causality between inflation and inflation... more This study investigates the asymmetric and time-varying causality between inflation and inflation uncertainty in South Africa within a conditional Gaussian Markov switching vector autoregressive (MS-VAR) model framework. The MS-VAR model is capable of determining both the sign and direction of causality. We account for the nonlinear, long memory and seasonal features of inflation series simultaneously by measuring inflation uncertainty as the conditional variance of inflation generated by recursive estimation of a Seasonal Fractionally Integrated Smooth Transition Autoregressive Asymmetric Power GARCH (SEA-FISTAR-APGARCH) model using monthly data for the period 1921:01 to 2012:12. The recursive, rather than a full-sample, estimation allows us to obtain a time-varying measure of uncertainty and better mimics the real-time scenario faced by economic agents and/or policy makers. The inferred probabilities from the four-state MS-VAR model show evidence of a time-varying relationship. The conditional (i.e. lead-lag) and regime-prediction Granger causality provide evidence in favour of Friedman's hypothesis. This implies that past information on inflation can help improve the one-step-ahead prediction of inflation uncertainty but not vice versa. Our results have some important policy implications.

The study evaluates the forecasting ability of models of South Africa's real fixed business non-r... more The study evaluates the forecasting ability of models of South Africa's real fixed business non-residential investment spending growth over the recent 2003:1-2011:4 out-of-sample period. The forecasting models are based on the Accelerator, Neoclassical, Cash-Flow, Average Q, Stock Price and Excess Stock Return Predictors models of investment spending. The Average Q, Stock Price and Return Predictors models appear more important in forecasting the behaviour of South Africa's business investment spending growth over the recent 2003:1-2011:4 out-of-sample period. The results from this study point to the important role of the stock market in promoting investment growth in South Africa, underscoring the need for stock market development. Also, stock market variables seem to play an increasingly important role in predicting investment spending behaviour in recent times.

Applied Financial Economics, 2014

This paper examines the existence of long memory in daily stock market returns from Brazil, Russi... more This paper examines the existence of long memory in daily stock market returns from Brazil, Russia, India, China, and South Africa (BRICS) countries and also attempts to shed light on the efficacy of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models in predicting stock returns. We present evidence which suggests that ARFIMA models estimated using a variety of estimation procedures yield better forecasting results than the non-ARFIMA (AR, MA, ARMA and GARCH) models with regard to prediction of stock returns. These findings hold consistently the different countries whose economies differ in size, nature and sophistication.

International Journal of Production Economics, 2015

Forecasting aggregate retail sales may improve portfolio investors" ability to predict movements ... more Forecasting aggregate retail sales may improve portfolio investors" ability to predict movements in the stock prices of the retailing chains. Therefore, this paper uses 26 (23 single and 3 combination) forecasting models to forecast South Africa"s aggregate seasonal retail sales. We use data from 1970:01-2012:05, with 1987:01-2012:05 as the out-of-sample period. Unlike, the previous literature on retail sales forecasting, we not only look at a wider array of linear and nonlinear models, but also generate multi-steps-ahead forecasts using a real-time recursive estimation scheme over the out-of-sample period, to mimic better the practical scenario faced by agents making retailing decisions. In addition, we deviate from the uniform symmetric quadratic loss function typically used in forecast evaluation exercises, by considering loss functions that overweight forecast error in booms and recessions. Focusing on the single models alone, results show that their performances differ greatly across forecast horizons and for different weighting schemes, with no unique model performing the best across various scenarios. However, the combination forecasts models, especially the discounted mean-square forecast error method which weighs current information more than past, produced not only better forecasts, but were also largely unaffected by business cycles and time horizons. This result, along with the fact that individual nonlinear models performed better than linear models, led us to conclude that theoretical research on retail sales should look at developing dynamic stochastic general equilibrium models which not only incorporates learning behaviour, but also allows the behavioural parameters of the model to be state-dependent, to account for regime-switching behaviour across alternative states of the economy.

SSRN Electronic Journal, 2014

This paper employs classical bivariate, slab-and-spike variable selection, Bayesian semi-parametr... more This paper employs classical bivariate, slab-and-spike variable selection, Bayesian semi-parametric shrinkage, and factor augmented predictive regression models to forecast US real private residential fixed investment over an out-of-sample period from 1983Q1 to 2005Q4, based on in-sample estimates for 1963Q1 to 1982Q4. Both large-scale (188 macroeconomic series) and small-scale (20 macroeconomic series) slab-and-spike variable selection, and Bayesian semi-parametric shrinkage, and factor augmented predictive regressions, as well as 20 bivariate regression models, capture the influence of fundamentals in forecasting residential investment. We evaluate the ex-post out-of-sample forecast performance of the 26 models using the relative average Mean Square Error for one-, two-, four-, and eight-quarters-ahead forecasts and test their significance based on the McCracken (2004, 2007) mean-square-error F statistic. We find that, on average, the slab-and-spike variable selection and Bayesian semi-parametric shrinkage models with 188 variables provides the best forecasts amongst all the models. Finally, we use these two models to predict the relevant turning points of the residential investment, via an ex-ante forecast exercise from 2006Q1 to 2012Q4. The 188 variable slab-and-spike variable selection and Bayesian semi-parametric shrinkage models perform quite similarly in their accuracy of forecasting the turning points. Our results suggest that economy-wide factors, in addition to specific housing market variables, prove important when forecasting in the real estate market.

African Journal of Agricultural Research, Nov 4, 2010

Resources Policy, 2021

Journal of Human Ecology, 2012

Journal of Housing Research, 2015

Journal of Housing Research, 2013

The Journal of Economic Asymmetries, 2018

Cogent Economics & Finance, 2016

Global Business and Economics Review, 2016

Working Papers, Dec 7, 2012

Empirica, 2015

Journal of Applied Economics, 2015

Cogent Economics & Finance, 2014

Emerging Markets Review, 2015

Applied Financial Economics, 2014

International Journal of Production Economics, 2015

SSRN Electronic Journal, 2014

Abstract This study investigates the asymmetric and time-varying causalities between inflation an... more Abstract This study investigates the asymmetric and time-varying causalities between inflation and inflation uncertainty in South Africa within a conditional Gaussian Markov switching vector autoregressive (MS-VAR) model framework. The MS-VAR model is capable of determining both the sign and direction of causality. We account for the nonlinear, long memory and seasonal features of the inflation series simultaneously by measuring inflation uncertainty as the conditional variance of inflation generated by recursive estimation of a Seasonal Fractionally Integrated Smooth Transition Autoregressive Asymmetric Power \{GARCH\} (SEA-FISTAR-APGARCH) model using monthly data for the period 1921:01 to 2012:12. The recursive, rather than full-sample, estimation allows us to obtain a time-varying measure of uncertainty and better mimics the real-time scenario faced by economic agents and/or policy makers. The inferred probabilities from the four-state MS-VAR model show evidence of a time-varying relationship. The conditional (i.e. lead–lag) and regime-prediction Granger causality provide evidence in favor of Friedman's hypothesis. This implies that past information on inflation can help improve the one-step-ahead prediction of inflation uncertainty but not vice versa. Our results have some important policy implications.