production economics; farm management; agricultural policy; agricultural environmental issues; tourism; regional planning; rural development; methodology; marketing of agricultural and food products; international trade; development; sport management
Mongolia is the second largest landlocked country, which has unique economic condition. This paper aims to examine Mongolian economic growth from 2000 until 2016 and identify its determinants. The growth was studied based on the growth rate of National Domestic Product. Initially, 20 macroeconomic variables are chosen and tested for the economic growth determinators such as; unemployment rate, human capital index, import growth, inflation rate, export growth, and interest rate, etc. The results showed that the growth rate of dollar exchange, inflation rate, and the growth rate of export were the main factors (81.4%). Mongolian GDP per capita and poverty rate were compared with other Asian lower-middle-economies, which are classified in the same classification as Mongolia. An increment of average salary was adjusted by the inflation rate, which showed the purchasing power declined in 2015. Statistics of Central Bank of Mongolia, Central Intelligence Agency, World Bank’s statistics, and the statistics from National Statistics Office of Mongolia are used for the research.
JEL Classification: H0, H30, H6, H70
This study provides a disaggregated analysis of the effects of monetary policy shocks on the agricultural sector in Nigeria from 1981Q1 to 2016Q4. The study utilized the generalized impulse responses and the normalized generalized forecast error variance decompositions from an underlying VAR model, which are order-invariant. The four monetary policy variables used in the study are interbank call rate, monetary policy rate, broad money supply and exchange rate; while the four agricultural sub-sectors investigated are crop production, forestry, fishing and livestock. The study also controlled for the general price level and other economic activities in the overall economy. The findings indicate that the aggregate agricultural sector and its various sub-sectors consistently responded negatively to unanticipated monetary tightening in most of the forecast horizon; while the immediate impact of monetary policy shocks is transmitted to the agricultural sector through the interest rate and money demand (credit) channels. The findings further indicate that apart from these two channels, the roles of monetary policy rate and exchange rate are non-negligible in the long-run. The role of money supply channel in spreading monetary policy shocks to the agricultural sector remained muted all through. The study concludes that the monetary authority should evolve interest rate, credit, and exchange rate policies that will promote the development of the agricultural sector in Nigeria.
JEL CODES: E52; N50; C22; N57
Access to credit is one of the critical areas that are of prime interest to development practitioners, agribusiness entrepreneurs and agricultural economists, mainly access to credit by farmers in order to increase their production and also reduce poverty. This study sought to analyze the determinants of credit access among cocoa farmers in the Asunafo North of the Ahafo Region of Ghana. The multistage sampling procedure was used to collect data from 100 cocoa farmers with the aid of a questionnaire. Sources of credit, factors influencing access to credit, and constraints to credit were analyzed with the aid of descriptive statistics, multiple linear regression, and Kendall’s coefficient of concordance respectively. The results of multiple linear regression revealed that, age, marital status, education, experience, and family size were significant factors that influenced access to credit. The constraints analysis with the aid of Kendall’s coefficient of concordance showed that, high interest rate was highly ranked with a mean score of 1.93 whilst the need for a guarantor was least ranked with a mean score of 7.40. Based on the results, the study recommended that a policy aimed at expanding formal and semi-formal financial institutions credit portfolio to embrace cocoa farmers by finding alternative to collaterals and also reducing the interest rate will improve credit access with a positive externality effect of poverty reduction among cocoa farmers in the study area.
JEL Classification: Q14
This study analyzes the transmission of systematic risk exhaling from macroeconomic fundamentals to volatility of stock market by using auto regressive generalized auto regressive conditional heteroskedastic (AR-GARCH) and vector auto regressive (VAR) models. Systematic risk factors used in this study are industrial production, real interest rate, inflation, money supply and exchange rate from 2000-2014. Results indicate that there exists relationship among the volatility of macroeconomic factors and that of stock returns in Pakistan. The relationship among the volatility of macroeconomic variables and that of stock returns is bidirectional; both affect each other in different dynamics.
JEL code: C32, C58, G11, G12
This study analyze the risk and return characteristics of commodity index investments against the LIBOR benchmark. Commodity-based asset allocation strategies can be optimized by benchmarking the risk and return characteristics of commodity indices with LIBOR index rate. In this study, we have considered agriculture, energy, and precious metals commodity indices and LIBOR index to determine the risk and return characteristics using estimation techniques in terms of expected return, standard deviation, and geometric mean. We analyzed the publicly available daily market data from 10/9/2001 to 12/30/2016 for benchmarking commodity indices against LIBOR. S&P GSCI Agriculture Index (SGK), S&P GSCI Energy Index (SGJ), and S&P GSCI Precious Metals Index (SGP) are taken to represent each category of widely traded commodities in the regression analysis. Our study uses time series data based on daily prices. Alternative forecasting methodologies for time series analysis are used to cross-check the results. The forecasting techniques used are Holt-Winters Exponential Smoothing and ARIMA. This methodology predicts forecasts using smoothening parameters. The empirical research has shown that the risk of each of the commodity index that represents agriculture, energy, and precious metals sector is smaller compared to its return, whereas LIBOR based interest rate benchmark shows higher risk compared to its return in recession, non-recession and overall periods.
JEL Classification: C43, G13, G15
Small and medium-sized enterprises form the engine of the Hungarian economy, both in terms of their number and their employment rate. Therefore, the efficient operation of this sector is in the interest of many economic actors. However, experience shows that today's SME sector still needs to develop in many ways to become efficient. This study aimed to analyze whether SMEs use the necessary methods and tools to be efficient. Planning and the development of strategy are very important methods and tools for efficient and organized work, as it defines and clarifies the direction taken by an enterprise. However, the survey and the in-depth interview showed that they are not necessarily considered important for the participating SME leaders. According to the interview, one of the reasons is that SME leaders have a better understanding of everyday tasks and their implementation than the managers of large companies. Furthermore, in most cases, the SME leader is personally involved in everyday work. This provides the advantage of having the opportunity to fully understand the enterprise, thus managing, and developing it more effectively, as he or she can intervene more flexibly, faster, and more accurately if necessary. However, due to the small size of the organization, the manager also must perform the tasks of several functions (marketing, management, finance, etc.), which require multidisciplinary knowledge and skill. In SMEs, due to their specificities, it is difficult to apply best practices in large enterprises in both management and various functions.
JEL code: M21