Past decades have witnessed evidence to large-scale upheaval caused by natural disasters. Thus, there is a need for determination of mechanisms through which natural disasters may influence growth, especially for developing countries. This paper traces the medium-short run time path of agricultural and industrial output growth response to four types of disasters in Southern and Southeastern Asian countries. Disasters considered are floods, droughts, storms and earthquakes. The empirical results suggest heterogeneous effects for disasters as well as different economic sectors. In many cases disaster impact was delayed. Generally speaking, floods and droughts have a stronger effect while earthquakes and storms have a weaker one on disaggregated output growth. Floods have a predominantly posi-tive effect while droughts have a negative one on both agricultural and industrial sectors. Storms seem to show a stronger negative effect in the agricultural sector than in industrial sector hinting at existence of short lived indirect effects. Earth-quakes, on the other hand, presented ambiguous growth responses. / No

<p>Past decades have witnessed evidence to large-scale upheaval caused by natural disasters. Thus, there is a need for determination of mechanisms through which natural disasters may influence growth, especially for developing countries. This paper traces the medium-short run time path of agricultural and industrial output growth response to four types of disasters in Southern and Southeastern Asian countries. Disasters considered are floods, droughts, storms and earthquakes. The empirical results suggest heterogeneous effects for disasters as well as different economic sectors. In many cases disaster impact was delayed. Generally speaking, floods and droughts have a stronger effect while earthquakes and storms have a weaker one on disaggregated output growth. Floods have a predominantly posi-tive effect while droughts have a negative one on both agricultural and industrial sectors. Storms seem to show a stronger negative effect in the agricultural sector than in industrial sector hinting at existence of short lived indirect effects. Earth-quakes, on the other hand, presented ambiguous growth responses.</p> / No

This paper explores the link between agriculture investment and agriculture output in Namibia. The existing theory on investment and growth constitutes a basis for empirical work on investment-output nexus. Neither the neoclassical nor the new growth theories on investment have considered the growth effects of investment at sector and industry level and its implication on capital allocation, particularly for developing countries that are resource constrained. The key question addressed in this paper is whether investment in agriculture is associated with agriculture output, both at the sector and sub-sector levels. The paper adopted the ARDL bounds test model constructed with quarterly data for the period 2000 to 2020 and found that investment and agricultural output exhibit a long-run relationship. The coefficient estimates showed that public investment, development bank loans and agriculture export have a positive impact on agricultural output while inflation, lending rates and commercial bank loans have a deleterious effect. The long-run causality tests suggest that there is unidirectional causality between commercial credit expenditure and aggregate agriculture output, as well as a unidirectional causality running from exports to livestock and crop sub-sector output. Based on error correction terms, agriculture output tends to rapidly adjust to short-term disturbances, hence rebound of agriculture output to a long-run growth path can take place with minimum or no delays. This study concludes that the Keynesian hypothesis is valid for Namibia's agriculture and the direction of causality is from investment to agriculture growth. Therefore, the role of government in supporting sustainable development of the agricultural sector cannot be overemphasised.

In the literature there are mixed results on the link between credit and agricultural output growth. Some authors argue that credit leads to growth in agricultural output. Others view growth as one of the factors that influence credit supply, thus growth leads and credit follows. By and large, studies have not endeavoured to establish the short-run impact of agricultural credit on output. They are generally limited in establishing the long-run relationship between credit and agricultural output and thus present a research gap in this respect. This study contributes to the existing body of literature by focusing on the finance-growth nexus at sectoral level as a departure from extant literature that has focused on the macroeconomic level. Using South African data, the study investigated the causal relationship between the supply of credit and agricultural output as well as whether the two are cointegrated and have a short-run relationship. The study found that bank credit and agricultural output are cointegrated. Using the error correction model (ECM), the results showed that, in the short-run, bank credit has a negative impact on agricultural output, reflecting the uncertainties of institutional credit in South Africa. However, the ECM coefficient shows that the supply of agricultural credit rapidly adjusts to short-term disturbances, indicating that there is no room for tardiness in the agricultural sector. The absence of institutional credit will immediately be replaced by availability of other credit facilities from non-institutional sources. Conventional Granger causality tests show unidirectional causality from (1) bank credit to agricultural output growth, (2) agricultural output to capital formation, (3) agricultural output to labour, (4) capital formation to credit, and (5) capital formation to labour, and a bi-directional causality between credit and labour. Noteworthy and significant for South Africa is that for the agricultural sector, the direction of causality is from finance to growth, in other words supply-leading, whereas at the macroeconomic level, the direction of causality is from economic growth to finance, in other words, demand-leading. Applying a structural equation modelling approach to survey data of smallholder farmers, the positive relationship between bank credit and agricultural output observed from analysis of secondary data was confirmed. / Business Management / DCOM (Business Management)

In the literature there are mixed results on the link between credit and agricultural output growth. Some authors argue that credit leads to growth in agricultural output. Others view growth as one of the factors that influence credit supply, thus growth leads and credit follows. By and large, studies have not endeavoured to establish the short-run impact of agricultural credit on output. They are generally limited in establishing the long-run relationship between credit and agricultural output and thus present a research gap in this respect. This study contributes to the existing body of literature by focusing on the finance-growth nexus at sectoral level as a departure from extant literature that has focused on the macroeconomic level. Using South African data, the study investigated the causal relationship between the supply of credit and agricultural output as well as whether the two are cointegrated and have a short-run relationship. The study found that bank credit and agricultural output are cointegrated. Using the error correction model (ECM), the results showed that, in the short-run, bank credit has a negative impact on agricultural output, reflecting the uncertainties of institutional credit in South Africa. However, the ECM coefficient shows that the supply of agricultural credit rapidly adjusts to short-term disturbances, indicating that there is no room for tardiness in the agricultural sector. The absence of institutional credit will immediately be replaced by availability of other credit facilities from non-institutional sources. Conventional Granger causality tests show unidirectional causality from (1) bank credit to agricultural output growth, (2) agricultural output to capital formation, (3) agricultural output to labour, (4) capital formation to credit, and (5) capital formation to labour, and a bi-directional causality between credit and labour. Noteworthy and significant for South Africa is that for the agricultural sector, the direction of causality is from finance to growth, in other words supply-leading, whereas at the macroeconomic level, the direction of causality is from economic growth to finance, in other words, demand-leading. Applying a structural equation modelling approach to survey data of smallholder farmers, the positive relationship between bank credit and agricultural output observed from analysis of secondary data was confirmed. / Business Management / D. Com. (Business Management)