Transaction costs and crop marketing in the communal areas of Impendle and Swayimana,KwaZulu-Natal

High transaction costs are detrimental to the efficient operation or existence of markets for inputs and outputs. The cost of information and the costs associated with the search for trade partners, the distance to formal markets and contract enforcement are likely to influence the marketing of food crops. This study hypothesises that the level of income generated from food-crop sales by small-scale farmers in the Impendle and Swayimana districts of KwaZuluNatal is influenced by transaction costs and certain household and farm characteristics. Regression analysis shows that the depth of marketing methods is significantly influenced by transaction cost proxies, such as cooperation with large commercial farmers and ownership of means of transport. Results from a block-recursive regression analysis show that the level of crop income generated is determined by the depth of marketing methods, the size of allocated arable land and off-farm income. Households with lower transaction costs, sizeable allocated land and off-farm income can be expected to generate higher income from food crops. Investment in public goods such as roads, telecommunications and an efficient legal system (to uphold commercial contracts), as well as farmer support services (input supply, extension, marketing information and research), would probably raise farm and non-farm income by reducing transaction costs. This would increase the effective demand for locally produced goods and services, thus contributing to rural employment and livelihoods within rural communal areas.     

Did Leaving the Gold Standard Tame the Business Cycle? Evidence from NBER Reference Dates and Real GNP

Cover and Pecorino (2005) claim that the March 1933 departure from the gold standard is the most probable break point ushering in an era of longer U.S. expansions, both absolutely and relative to subsequent recessions. Their analysis is based on cycle durations as defined by National Bureau of Economic Research (NBER) reference dates. However, much of macroeconomic analysis is based on (i) growth cycles (i.e., periods when the economy's production is above or below trend) rather than absolute increases or decreases in economic activity; and (ii) aggregate time series' volatility as the prime indicator of macroeconomic stability. In light of this, we reevaluate the March 1933 break point. First, using HP‐filtered quarterly gross national product (GNP), our analysis of growth cycle durations still implies a break point near 1933. Second, we test for structural breaks in the volatility of GNP growth rates and deviations from trends. These tests suggest a structural break considerably later than 1933, perhaps as late as the 1950s.