Forecast evaluations in meat demand analysis

This article examines the long‐ and short‐run effects of rural credit on the gross value added of agricultural output in Brazil. We apply the dynamic vector error correction model (VECM) to the estimation and testing. The main finding is that there is a positive long‐run relationship between agricultural sector production and loans from financial institutions to the agricultural sector. The long‐run elasticity estimated was 0.44, implying that an increase of 1% in rural credit leads to a 0.44% increase in the agricultural sector's GDP. This result supports the policy of rural credit as a crucial institutional instrument to strengthen the agricultural sector and as an important factor to boost the country's economic growth.

A country has several important parameters to achieve economic prosperity, such as tax revenue and inflation rate. One of the largest revenues of the State Budget in Indonesia comes from the tax sector. Meanwhile, the rate of inflation occurring in a country can be used as an indicator, to measure the good and bad economic problems faced by the country. Given the importance of tax revenue and inflation rate control in achieving economic prosperity, it is necessary to analyze the structure of tax revenue relations and inflation rate. This study aims to produce the best VECM (Vector Error Correction Model) with optimal lag using various alpha and perform structural analysis using the Impulse Response Function (IRF) of the VECM models to examine the relationship of tax revenue, and inflation in Banda Aceh. The results showed that the best model for the data of tax revenue and inflation rate in Banda Aceh City using alpha 0.01 is VECM with optimal lag 2, while the best model for data of tax revenue and inflation rate in Banda Aceh City using alpha 0.05 and 0,1 VECM with optimal lag 3. However, the VECM model with alpha 0.01 yielded four significant models of income tax model, inflation rate of Banda Aceh, inflation rate of health and inflation rate of education in Banda Aceh. While the VECM model with alpha 0.05 and 0.1 yielded one significant model that is income tax model. Based on the VECM models, then there are two structural analysis IRF which is formed to look at the relationship of tax revenue, and inflation in Banda Aceh, the IRF with VECM (2) and IRF with VECM (3).

The study examines the effects of current account deficits on economic growth. It also evaluates the direction of causality between the current account deficits and economic growth. These have in the recent past been analyzed in developed and developing economies. In contributing to this ongoing debate, the study applied unit root tests, cointegration analysis, a dynamic vector error correction model and Toda-Yamamoto Granger-causality representation using annual time series data for Kenya from 1980 to 2016. There is evidence that in the long run, current account deficit has significant positive effect on economic growth in Kenya. The evidence suggests a bidirectional causality running from current account deficit to economic growth with feedback effects. The study underscores the need for the authorities to utilize current account deficits to strictly finance public investment to foster gross fixed capital formation, for shared prosperity in Kenya. The evidence underscores the need for more country specific studies in sub-Saharan Africa.

Vector Error-Correction Model (VECM) is a method of statistical analysis frequently used in many studies in time series data of economy, business and finance, and data energy. It is applied across researches due to its simplicity and limited restrictions. VECM can explain not only the dynamic behavior of the relationship among variables of endogenous and exogenous, but also among the endogenous variables. Moreover, it also explains the impact of a variable or a set of variables on others by means of Impulse Response Function and Granger Causality analysis. It can also be used for forecasting multivariate time series data. In this research, the relationship of three share price of energy (from three Asean countries: PGAS Malaysia, AKRA Indonesia, and PTT Thailand) will be studied. The data in this study were collected from October 2005 to August 2019. Based on the comparison of some VECM models, it was found that the best model is VECM (2) with cointegration rank=3. The dynamic behavior of the data is studied through Impulse Response Function (IRF), Granger Causality analysis and forecasting for the next five periods(weeks). Keywords : Cointegration, VAR model, VECM model, Granger Causality, Impulse Response Function, Forecasting. JEL Classifications : C32, Q4, Q47 DOI: https://doi.org/10.32479/ijeep.8946

Financial performance is crucial in making strategic decisions and is highly used by managers to outline their future operations. In large-scale companies like energy companies analyzing financial performance is of utmost importance. In this regard, the present study attempts to evaluate the financial performance of DANA GAS Company in Iraq from 2007Q1 to 2021Q4 using a Vector Error Correction Model (VECM). The study contributes to a better understanding of the relationships between financial indicators and revenue growth in the energy sector. The VECM approach provides a useful tool for evaluating financial performance, allowing companies to identify areas for improvement and make data-driven decisions. The analysis reveals significant long-term relationships between financial indicators and revenue growth. Profitability, return on assets and liquidity with the company's revenue growth. However, the return on equity shows a negative sign, while the company size is insignificant. The findings have implications for strategic decision-making and financial management practices aimed at enhancing Dana Gas Company's financial performance and resilience in dynamic market environments

This research was conducted to determine the short-term and long-term effects of inflation, exchange rates, interest rates, and the money supply on economic growth in Indonesia from 2009 to 2022 using the Vector Error Correction Model (VECM) method. The VECM method is used to analyze the interaction between these variables over different time horizons, offering valuable insights into their respective roles in influencing economic growth. The results show that in the short run, the exchange rate variable does not have a significant effect on the economic growth, while in the long run the interest rate variable has a positive impact on the economy with a negative coefficient value. The short run variable interest rates do not have significant effects on the growth of the economy, but in the longer run interest rates have an important effect on growth. In conclusion, the effect of exchange rates on the Indonesian economy is still a controversial research topic. The findings enhance the current literature on macroeconomic policy and provide a foundation for policymakers to design more effective economic strategies, especially in addressing the challenges posed by inflation and exchange rate volatility in both the short and long terms.

This study aims to analyze the relationship between the level of farmers’ welfare between agricultural subsectors in Indonesia in the short and long term using the Vector Error Correction Model (VECM) approach. The data used includes the Farmer Exchange Rate (NTP) from five subsectors: Food, Hor ticulture, Plantations, Farms, and Fisheries. The results of the study show that there are differences in the relationship between subsectors in the short and long term. In the long term, Food NTP, Horti culture NTP, and Plantation NTP affect each other significantly, both positively and negatively, while Farms NTP and Fisheries NTP tend to have a more limited influence. On the other hand, short-term relationships are more influenced by NTP values from previous periods. The VECM model proved to be accurate in modeling the relationship between subsectors, with the Mean Absolute Percentage Error (MAPE) value of all subsectors being below 10%. In detail, MAPE for Food NTP is 2.18%, Horticulture NTP 4.18%, Plantation NTP 3.43%, Farms NTP 0.71%, and Fisheries NTP 0.86%. Thus, the VECM model is effectively used to analyze the dynamics of farmers’ welfare between subsectors in Indonesia.

Macroeconomic Impact on Stock Market Returns and Volatility: Evidence from Sri Lanka

This study aims to analyze the spatial market integration of beef prices in supporting the stabilization of prices for basic livestock products in Jambi Province. Spatial Market Integration Analysis Beef prices in Jambi Province use secondary data which is weekly time series data for the period 2018 – 2021 (August). The data analyzed in this study is the price of beef in the markets of Jambi City and Bungo Regency. The analytical method used to see the level of spatial integration of the beef market in supporting the stabilization of livestock staples both in the short and long term in Jambi Province is the VAR (Vector Autoregression) / VECM (Vector Error Correction Model) model. The study concludes that the weekly average beef price in Jambi City and Bungo Regency during the period 2018 to 2021 (August) is cointegrated. There is a long-term relationship between weekly average beef prices in Jambi City and Bungo Regency. The VECM model is more accurate in forecasting the weekly average beef price in Jambi City and Bungo Regency in the future.

The role of banks as intermediary institutions have to be improved continually so that they are in line with Indonesia’s economic growth which is also experiencing significant fluctuations. This study aims to analyze banking indicators, namely banking technology indicators as measued by Bank Indonesia Real Time Gross Settlement (BIRTGS) and electronic money, banking assets, loans, exchange rates, BI interest rates (BI-rate) and the industrial sector on economic growth in Indonesia. This study uses the Vector Error Correction Model (VECM) to analyze two banking indicators, namely assets, loans, two indicators of banking technology, namely BI-RTGS, electronic money, as well as Birate (BI interest rate), exchange rates and gross domestic product in the industrial sector from 2010 to 2022. The results of data analysis using impulse response function (IRF) graphs show a positive response from economic growth to the shock of asset, loan, and electronic money. BI-rate and BI-RTGS variables show a negative response to economic growth, but affect economic growth consistently. Overall, it can be concluded that all variables are shown to have an influence on economic growth as indicated by the optimal lag obtained in the VECM model over 2 quarters. The novelty and main contribution of this study is the use of BI-RTGS and electronic money as a proxy for banking technology. Currently, little research has been done on the link between banking technology and economic growth rates.

This study examined the effect of foreign aid on both economy and investment of Ethiopia from time 1974 to 2014. The empirical analysis has been done using multivariate co integration analysis of both vector autoregressive model (VAR) and (Vector error Correction model (VECM). Both models which enables to capture short run dynamics. VECM model is constructed by restricting long run behavior of endogenous variables for allowing for short run adjustment dynamics. The co integrating vector which is deviation from the long run equilibrium corrected through series of partial short run dynamics, which is known as error correction term The main findings of the study shown foreign aid has a significant positive effect on economic progress in both lengthy run and squat run. On other hands, aid has irrelevant and optimistic effect on gross domestic investment in both extensive time and short run. Further, the findings discovered that there is unidirectional causality among foreign aid to economic growth and foreign aid to gross domestic investment. Based on the findings the study recommends aid should be used to support the shortage of resource gap; also, aid should be focused on growth enhancing sectors as well as poverty reduction policies, then it will rise savings of societies'.

The French government has recently decided to increase the Photovoltaic (PV) capacities to reach 35GW by 2028 in all french territories, the European territory, and overseas territories such as Reunion Island in the Indian Ocean. However, integrating growing numbers of PV power installations and microgrids onto the grid can result in larger-than-expected fluctuations in grid frequency. This is due to PV power output that is not only a function of the operating temperature and solar irradiation but also of other environmental parameters. In this paper, only two environmental parameters are considered in the European zone and when the Engle & Granger statistical method is used, a relationship between variables such as photovoltaic power output and solar irradiation at a different level is obtained. The final relationship without suspicious heteroscedasticity is determined. The model is formulated on the basis of photovoltaic real conditions statistical approach and is more realistic than steady approach models. The Engle & Granger method does not distinguish several cointegration relationships when more variables are considered. For the overseas zone, we added other measured environmental variables and applied a more robust statistical method known as the Johansen vector error correction model (VECM) cointegration approach. In the VECM model, for N explanatory variables and for N > 2, we established a long-run equilibrium relationship that has been tested and the outcome is more than reliable when comparing the model to measured data.

Purpose: This study examines the short-run and long-run impact of the expansionary fiscal policy on economic growth in Zambia from 1991 to 2021. Materials and Methods: The study employs the Vector Error Correction Model (VECM) and Auto Regressive Distributed Lag (ARDL) Models to examine the short-run and long-run impact of total public expenditure, total tax revenue and total public debt time series data on the gross domestic product (GDP) of Zambia from 1991 to 2021. The Keynesian theory informed our study, which presupposes that the unemployment problem might be solved by boosting government spending on consumption and that government spending was an exogenous factor that contributed to economic growth (Keynes, 1936; Singh & Sahni, 1984). Findings: Both the VECM and ARDL Models show the existence of statistically significant long-run cointegration among public expenditure, external debt, tax revenue and GDP. Specifically, VECM estimates show that for a 1% increase, Tax revenues have a positive long-run significant effect on Zambia’s economic growth of 3.36%, while external debt and public expenditure have significant negative effects on the economic growth of 1.17% and 0.003% in Zambia respectively. The ARDL model estimates indicate that, in the short run, an increase in tax revenue of 1% increases GDP growth by 1.92%, while a rise in government expenditure and external debt by 1% results in a decline in Zambia’s economic growth by 0.003% and 6.14% respectively. Implications to Theory, Practice and Policy: Given the foregoing findings, the therefore study recommends that the Government of Zambia should widen the tax base to mobilize more tax revenues and reduce the budget deficits emanating from high government expenditures. External public debt should also be reduced.

With the ever-growing importance of stock markets, an overwhelming number of studies have been carried out worldwide to investigate the link which exists between stock market development and economic growth. However, studies analyzing this link are scant in the African region. As such, this chapter uses a dynamic panel vector error correction model (PVECM) to analyze the relationship among stock market development, banking development, and economic growth in a unified framework for the period 1988–2011. The results suggest that stock market development plays an important role in generating gains in terms of economic growth both in the short run and in the long-run within the sample of African countries under consideration.

Institutional and market frictions impose costs on the reallocation of labor from low to high productivity sectors, leading to suboptimal allocations and a loss in aggregate labor productivity. Using cross-country sector-level data, we use a dynamic panel error correction model to compute the speed of sectoral labor adjustment, as well as the contribution of structural reforms in governance, labor and product markets, trade and openness, and the financial sector to lowering the costs of labor reallocation. We find that, on average, sectoral employment shares converge towards equilibrium allocations, closing about 13.7 percent of labor productivity gaps each year; this speed of labor adjustment varies across sectors and income groups. On structural reforms, we find a significant association between more efficient labor reallocation and financial market liberalization, less bureaucracy, strong judicial and regulatory environment, trade liberalization, better education and more flexible labor and product markets.