This dissertation addresses: 1) the reliability of El Niño Southern Oscillation (ENSO) forecasts generated by the International Research Institute for Climate and Society (IRI) of Columbia University; 2) estimation of parameters of Mexican crop demand; and 3) the potential impacts of climate change on Mexican agriculture. The IRI ENSO forecasts were evaluated using prequential analysis, with calibration and scoring rules. Calibration tests and the Yates’ decomposition measures of the Brier score suggest that the IRI ENSO forecasts are improving in reliability and skill, showing a learning by doing behavior, i.e., these IRI ENSO forecasts show improved ability to predict the ENSO phases that really happen. In terms of estimation of the parameters of Mexican crop demand, an LA/AIDS model was used but the results were not very satisfactory with statistical tests rejecting homogeneity and symmetry. Furthermore, the estimated uncompensated price and income elasticities were found to be located in the tail regions of the Monte Carlo simulated density functions, showing poor validation of the initial estimates under similar economic (price and consumption) circumstances. Finally, in terms of the potential impacts that climate change has on Mexican agriculture, two 2050 climate change scenarios were examined. The central result indicates that Mexico benefits from climate change under the IPCC ensemble results for the B1 scenario and would experience welfare losses under the ensemble results for the A2 scenario. Moreover, dryland hectareage would decrease and would be replaced by irrigated areas. Finally, producer’s net income was found to decrease at the national level under both climate change scenarios. The results were generated using a mathematical programming sector model that was updated for the study.

A number of developing countries have been on a quest to attract foreign direct investment (FDI) with the intention of increasing capital inflow through technological spillovers and transfer of managerial skills. FDI can increase economic growth and development of a country by creating employment, and by doing so, increasing economic activity that will lead to economic growth. South Africa is one of the economies that strive to attract more FDI inflows into the country to be able to improve its economy, and the country has adopted policies that drive the motive to attract FDI inflows. This study investigated the effect of FDI on sectoral growth over the period 1970–2014. The purpose was to find out where in the three key sectors of South Africa FDI is more significant. The review of theoretical and empirical literature on FDI revealed that FDI has a diverse effect on economic growth, both in developed and developing countries. Theoretical literature analysed the behaviour of multinational firms and the motive behind multinationals investing in foreign countries. According to Dunning (1993), firms have four motives to decide to produce abroad, namely natural resource-seeking, market-seeking, efficiency-seeking and strategic asset-seeking. Empirical studies on sectors show that FDI inflows affect different sectors in different ways, and that the agricultural sector does not usually gain from FDI inflows, whereas subsectors in the industry and services sector grow from receiving FDI inflows. Sectoral analysis revealed that the services sector receives more FDI inflows, when compared to the agriculture and industry sector. The study followed an econometric analysis technique to test the effect of FDI inflows on the agriculture, industry and services sectors. The augmented Dickey–Fuller and Phillips–Perron tests were used to test for unit root. Both tests revealed that variables were not stationary at level, but that they become stationary at first difference. Vector autoregressive (VAR) models were estimated, and four types of diagnostic tests were performed on them to check the fitness of the models. The tests showed that residuals of the estimated VARs were robust and well behaved. The Johansen cointegration test suggested there is cointegration and that there is a long-run relationship between variables. Following the existence of cointegration, the estimated Vector error correction model (VECM) results showed that FDI has a significant effect on the services and industry sector, but has a negative effect on the agricultural sector. Impulse response analysis results revealed the correct signs, and confirmed the VECM results. FDI inflows explain a small percentage of growth in agriculture and industry, but a sizable and significant percentage in the services sector. / Economics / M. Com. (Economics)

D. Tech. (Department of Information and Communication Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. / The agriculture sector is the lifeblood of the economies of the world's least developed countries (LDCs). In Zimbabwe, this sector is considered to be the backbone of Zimbabwe's economy, and as a result, it is the sector that supports the economic growth of the country, food security, and poverty eradication efforts. Furthermore, the use of mobile technology has continued to rise in Zimbabwe, and farmers now can obtain agricultural information through the use of mobile technology. Mobile phones are increasingly being integrated into current agricultural trade businesses, owing to the critical role they serve in facilitating information transmission between farmers and buyers. The potential of mobile phones in agriculture spawned mAgriculture, which is the use of mobile phones to provide agricultural information and services. Variousitechnology companies in iZimbabwe have come up with various mobile farming platforms as innovation, with the aim of improving overall performance among smallholder farmers. In order to find the usefullness of these mobile farming platforms, it imperative to measure the adoption and acceptance of this technology in the farming environment. The study sought to investigate the adoption and acceptance of mobile farming platforms in Zimbabwe through a more comprehensive model based on UTAUT 2 that encapsulates the key factors that influence user adoption and acceptance of mobile farming platforms. The main aim of the study was to inform technology start-up companies and other mobile application developers in the development of mobile farming platforms or applications that can be fully adopted and accepted by users, taking into cognisance all salient factors affecting their adoption and acceptance. The model has been used to investigate smallholder farmers in a developing country such as Zimbabwe. The model explores the effect of attitude as one of the key determinants that affect the behavioral intention to use mobile farming platforms. In addition, the model looked at the moderating effect of Hofstede's five cultural dimensions on the key determinants that influence behavioral intention as well as actual use of mobile farming platforms at individual level. A total of 411 questionnaires were received from smallholder farmers in Zimbabwe's three major provinces who were using mobile farming platforms. Structural Equation Modelling was utilized to test the hypothesized conceptual model. Reliability and validity checks were done to the model instrument. As hypothesized, the findings of this study revealed that performance expectancy (PE), effort expectancy (EE) and facilitating conditions (FC) are significant determinants of the newly added variable Attitude (AT). Attitude (AT), together with social influence (SI), facilitating conditions (FC), hedonic motivation (HM), price value (PV), and habit (HB) were found to be significant determinants of behavioral intention and usage of mobile farming platforms for smallholder farmers. The results also showed that cultural dimensions have a moderating effect on user acceptance of mobile farming platforms. According to the findings, attitude and culture are significant factors to consider when analyzing farmers' behavioral intentions and use of mobile farming platforms. The findings of the study contribute to the literature by validating and supporting the applicability of the extended UTAUT 2 for the adoption and acceptance of mobile farming platforms by smallholder farmers in developing countries. The theoretical contribution of the study was through the extension of UTAUT 2 where attitude was added as one of the new key determinants of behavioral intention and cultural dimensions were added as mediators. The other contribution is to the Zimbabwean farming community where the study was conducted.