Effect Of Macroeconomic Factors Research Articles

The effects of macroeconomic factors on South African agriculture

Significant research efforts have been devoted to understanding the effects of macroeconomic factors on the agriculture sector. Analysing the sources of volatility in the industry is critical for designing appropriate policies to stabilize agricultural markets, reduce poverty and increase economic growth. Agriculture is a competitive sector with prices that are more flexible than those in nonagricultural sectors. This article uses annual data over the 1957–2004 period and a vector error-correction model in investigating the dynamic effects of exchange rates, money supply and other macroeconomic variables on the agricultural sector in South Africa. Overall, real exchange rates, interest rates, inflation and money supply (M3) shocks have significant and persistent impacts on agricultural output, prices received by farmers and farm input prices. M3 and interest rate shocks tend to put agriculture in a cost-price squeeze. Agricultural price movements are a source of macroeconomic instability in the country. Real exchange rate shocks shift relative prices in favour of agriculture in the long-run, thereby, boosting farm incomes and accelerating poverty reduction in the country.

Analisis Dampak Kurs Mata Uang Inflasi dan Pertumbuhan Ekonomi terhadap Return Saham: Studi pada Ferusahaan Multinasional di Bursa Efek Jakarta

The main objective of this study is to provide empirical evidence of the effect of macro economic factors on stock return. Moreover, this study is focused on multinational corporations due to their specific characteristics which are constantly reluctant to macro economic fuctors, especially foreign currency changes. This reluctantly, therefore triggered stock price changes.The sample is taken using non-probability random sampling in year 2000-2044 and resulted on 3 5 companies which are consistent with sample criteria. Subsequently, the data were analyzed using pooled least squares regression.The independent variables for the model are inflation, gross domestic product and currency exchange rates, whilst the dependent variqble for the model is daily abnormal returns which ore occumulated during a year (CAR). The resultof this study shows positive ffict of inflation on stock returns and negative effect of domestic product on stock returns. On the contrary, exchange rates failed to demonstrate its effect on stock returns.Key words: inflation, gross domestic product, exchange rotes and stock returns

Macroeconomic risk factors in Australian commercial real estate, listed property trust and property sector stock returns

This paper employs a Generalised Autoregressive Conditional Heteroske‐dasticity in Mean (GARCH‐M) model to consider the effect of macroeconomic factors on Australian property returns over the period 1985 to 2002. Three direct (office, retail and industrial property) and two indirect (listed property trust and property stock) returns are included in the analysis, along with market returns, short, medium and long‐term interest rates, expected and unexpected inflation, construction activity and industrial employment and production. In general, macroeconomic factors are found to be significant risk factors in Australian commercial property returns. However, the results also indicate that forecast accuracy in these models is higher for direct office, listed property trust and property stock returns and that the persistence of volatility shocks varies across the different markets, with volatility half lives of between five and seven months for direct retail and industrial property, two and three months for direct office property and less than two months with both forms of indirect property investment.

Modèles à changement de régime et test de la théorie des anticipations rationnelles de la structure par terme des taux d’intérêt en France

L'étude empirique de la dynamique du taux d ’ intérêt de long terme , par l ’ intermédiaire de la méthodologie développée par Campbell et Shiller (1987 ), a conduit le plus souvent à observer une sur-réaction du spread observé par rapport à l ’ évolution prédite par la théorie des anticipations rationnelles , en particulier pour les États-Unis . Cependant , ce résultat repose sur une spécification particulière du comportement du taux d ’ intérêt de court terme . Nous poursuivons ici un double objectif . Tout d ’ abord , nous cherchons à savoir si l ’ utilisation des modèles à chaîne de Markov , par la prise en compte d ’ éventuels changements de régime au niveau du processus stochastique suivi par le vecteur autorégressif , permet une meilleure validation de la théorie pour la France . Nous analysons ensuite l ’ importance de l ’ attitude des facteurs macroéconomiques sur le découpage produit par ces modèles . L ’ utilisation d ’ un VAR à chaîne de Markov permet , d ’ une part , d ’ obtenir une meilleure validation statistique de la théorie des anticipations et , d ’ autre part , de souligner l ’ influence du taux de change entre le franc et le deutschemark sur les résultats obtenus

The Stock Market Perception of Industry Risk and Macroeconomic Factors: The Case of the US Water and Other Transportation Stocks

This paper attempts to uncover and compare the macroeconomic determinants of the stock returns of US listed water transportation companies to those of other transport sectors over the period July 1985 – June 1995; these involve air transportation, rail transportation and trucks. Other non-transport sectors such as electricity, gas, petroleum refining and real estate are also examined. This is done by relating cross-sectional differences in the returns of the companies in each industry to the stock market and to the following set of macroeconomic factors: (1) industrial production; (2) the term structure of interest rates; (3) oil prices; (4) consumption; and (5) inflation. Multivariate Least Square (MLSQ) regression methods are employed to estimate the above relationships. Important findings of this paper are: First, the effect of macroeconomic factors on stock returns varies among transportation industries and the other industries examined. Second, the stock market return influences the returns of all industries. Third, the market beta of the water transportation industry does not appear to be significantly higher, or lower, than the market beta of the remaining transportation, and non-transportation, sectors analysed.

The Usefulness of Economic Value-Added in the Australian Context

This paper employs a Generalized Autoregressive Conditional Heteroskedasticity in Mean (GARCH-M) model to consider the effect of macroeconomic factors on Australian property returns over the period 1985 to 2002. Three direct (office, retail and industrial property) and two indirect (listed property trust and property stock) returns are included in the analysis, along with market returns, short, medium and long-term interest rates, expected and unexpected inflation, construction activity and industrial employment and production. In general, the macroeconomic factors examined are found to be significant risk factors in Australian commercial property returns. However, the results also indicate that forecast accuracy in these models is higher for direct office, listed property trust and property stock returns and that the persistence of volatility shocks varies across the different markets, with volatility half lives of between five and seven months for direct retail and industrial property, two and three months for direct office property and less than two months with both forms of indirect property investment.