Industrial Sector Output Research Articles

Long and Short-Run Relationship Between Agricultural and Industrial Sectors’ Growth in Ethiopian Economy: Application of the Co-Integration and Error Correction Model (ECM)

The objective of this paper was to examine an equilibrium long run relationship and short impact of agricultural sector on the industrial sector and to determine the direction of causality in Ethiopia's economy using annual time series data ranging from 1991-2015 obtained from the World Development Indicators (WDI) database. The time was related to the implementation of the Ethiopian agricultural led industrialization (ADLI) strategy policy to food security and poverty reduction objectives of the country. The Johansen Co-integration test result showed that the data were co-integrated of the ordered one. The Johansen’s co-integration tests, both trace and max-trace statistical tests was significant at 1% critical values indicated that there was a strong long-run equilibrium relationship between agricultural and industrial sectors. The Johansen restricted normalized equations error correction model (ECM) indicated that agricultural has long run positive significant impact on industrial sector but not vice versa. Marginal analysis result indicated that increases agricultural by one percent, being other factors held constant, the industrial sector output increase by 3.39% due to economic multiplier effect. Granger pairwise causality test revealed that there exists unidirectional causality from industry to agriculture sector. In the long-run growth come from agriculture to industry and in the short run agricultural growth is caused by industry. Therefore, ADLI economic growth strategy should strengthened the sectors forward and backward linkages to bring balance and rapid sectorial growth that support the entire economic growth of the country. Keywords :ADLI, Co-Integration, Ethiopia, Industry, Integration, VECM. DOI: 10.7176/JESD/12-1-02 Publication date: January 31 st 2021

An Econometric Investigation of Sectoral Output and Environmental Degradation in Pakistan

This study examines effect of sectoral output (agriculture, industry and services) on environmental degradation in Pakistan ranging from period 1972 to 2017. This study makes use of Augmented Dickey Fuller test (ADF) followed by Autoregressive distributed lag model (ARDL). The empirical results show that Co2 emission in Pakistan is increased by Industrial sector output, population and energy consumption while agriculture sector output, services sector output and exports are reducing carbon dioxide emission.

Upshot of Foreign Capital Flows on Real Sector Growth in Nigeria

This study examines the upshot of foreign capital inflows on real sector growth in Nigeria from 1986 to 2019. The study sets out to achieve the effect of foreign direct investment (FDI), foreign portfolio investment (FPI), and official development assistance (ODA) on real sector growth in Nigeria. The study employed the SVAR model to achieve the study objective and the data sets used for this study were secondary sources. The study found that the inflows of FDI and ODA influence the industrial sector output significantly than the agricultural sector, thereby making the sector unattractive to foreign investors. The study concludes that inflows of foreign direct investment and official development assistance exert influence on industrial sector output than the agricultural sector. The study recommends that policymakers must develop policies that are foreign agricultural capital friendly to attract more foreign capital to the agricultural sector for the growth of economic activities in the industry.

Agricultural Sector Linkage with Other Sectors of the Economy: Evidence from Nigeria

Economic resource planners have continued to harness proven empirical link amongst various sectors of the economy for effective policy formulation and implementation of successful growth and development strategies. The Agricultural sector is one of the sectors that have consistently contributed to other sectors of the economy in terms of provision of raw materials, food and employment to the growing population; however, the need to understand the forward and backward linkages between the agricultural sector output and other sectors’ output has prompted this study. This paper investigates the causal link between the Agricultural sector output and Industry, Construction, Trade and Services sectors output using quarterly times series data extracted from the annual statistical bulletin of the Central Bank of Nigeria from the first quarter 2010 to the fourth quarter 2018. The study departs from the traditional static Leontief Input-Output approach by employing dynamic modern techniques like the Granger Causality, Vector Autoregression, Impulse Response and Variance Decomposition analyses. The results indicate the existence of bi-directional causal chain effect linkages between agricultural sector output, services, construction and trade outputs while a unidirectional causal linkage is found running from industrial sector output to agriculture. All the sectors drive agricultural sector output and agriculture stimulates other sectors except the industrial sector. In specific terms, it takes approximately two to four quarters for most sectors to respond to the impact of shocks emanating from the other sectors the economy. For the agricultural sector to play its pivot role as the driver of other sectors the study suggests that should be remodeled in such a way that its outputs meet industrial sector requirement.

Inter-state Growth Spillovers in Indian Major States: An Empirical Analysis

This article verifies the inter-state linkages of economic growth across Indian states in a panel framework. Data have been used for the 15 major states for 1980–1981 to 2013–2014. For studying the long-run association between aggregate output of a state and that of the rest of the states, panel cointegration techniques have been used. Fully modified ordinary least squares estimation technique is used to find long-run coefficients. In addition to it, inter-state growth spillovers of output for three principal sectors of economy have been verified separately. The findings confirm the existence of inter-state association in the long run for the aggregate output as well as the sectoral output. Unidirectional causality runs from rest of the state’s output to a state’s output. There has also been a substantial increase in the extent of linkages after the reforms for the aggregate output. Though coefficient is positive, agricultural output has witnessed a decrease in the extent of linkages after the reforms. But, the linkages among states for industrial and service sector output have been improved as a result of the reforms. With the increasing flow of goods and services, growth spillovers are evident and economic spillovers of states are complementary. Removing barriers on inter-state trade, flow of investment, knowledge, and services will supplement to growth spillover among Indian states.

The Contribution of Fiscal Policies to the Industry Sector

Fiscal policy is an adjustment in government revenue and expenditure as stipulated in the state revenue and expenditure budget in order to achieve better economic stability and pace of development. Several studies have shown that there is a relationship between fiscal policy and industrial sector output. The main objective of this study is to measure and analyze the contribution of fiscal policy on the industrial sector. The variables used in this research are industrial sector GDP, BI interest rate, government expenditure and tax revenue. The appropriate model for time series data that is not stationary is the Vector Error Correction Model (VECM). The data used are quarterly data from 1999 to 2019. The empirical results show that the industrial sector has a positive response to the shock of tax revenue variables and the consumer price index. On the other hand, the industrial sector responded negatively to shocks from government spending and the BI interest rate. The results of the variance decomposition analysis show that government spending provides the largest contribution to the industrial sector compared to other variables in this study.

Capital Market Performance and Sectoral Output Growth in Nigeria (1984-2016)

This study was carried out to investigate the effects of capital market performance on sectoral output growth in Nigeria within a temporal scope 1984-2018. The study was anchored on Ayodeji-Ajala (2018) capital market economic significance theorem; and as such, the independent variable, capital market performance, was measured by seven indicators, which are all-share index, market capitalization, number of listed equities, number of deals, stock market turnover, value of deals and value of transactions. However, to measure the dependent variable, sectoral output growth, five different models were developed, such that their respective dependent variables are contribution of agricultural sector to Gross Domestic Product (GDP), contribution of industrial sector to GDP, contribution of construction sector to GDP, contribution of trade sector to GDP, and contribution of service sector to GDP. With respect to these proxies, the study sourced annualized time-series data from the capital market bulletins of the Nigerian Securities and Exchange Commission and the statistical bulletins of the Central Bank of Nigeria, and estimated them using auto regressive distributed lad model. The study found that, on the effects of capital market performance on agricultural sector output, ASI, MCAP, VTRAN and NLE exerted significantly positive long-run effects on agricultural sector output in Nigeria. It, also, found that, on the effects of capital market performance on industrial sector output, MCAP and NOD exerted significantly positive long-run effects on industrial output in Nigeria. It, further, found that, on the effects of capital market performance on construction sector output, only MCAP exerted significantly positive long-run effects on construction sector output in Nigeria. Moreover, it found that, on the effects of capital market performance on trade sector output, only MCAP exerted significantly positive long-run effects on trade sector output in Nigeria while ASI, VTRAN and NOD exerted insignificantly positive long-run effects on it. Lastly, it found that, on the effects of capital market performance on service sector output, none of the capital market performance indicators exerted significantly positive long-run effects on service sector output in Nigeria. The study concluded that, capital market performance exerts heterogeneous long-run effects on sectoral output. It was, therefore, recommended that, government, at all levels, should focus more on agricultural development initiatives and strategies, as the sector manifests high tendency to respond significantly positively to capital market incitements in the long-run, much more that the sector is the largest employer of labour in Nigeria. Also, more government efforts, resources and attention should be geared toward the upgrading of market infrastructure, and toward the sanitization of Nigeria’s capital market against market infractions and insider abuses so as to boost the efficiency and liquidity performance of the market so that its effects can be noticeably felt on the industrial, construction, trade and service sectors of the economy.

Time-varying effect of the financialization of nonferrous metals markets on China's industrial sector

Based on the model of time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV), we incorporate the financialization of nonferrous metals markets into the analytical framework of multistructural nonferrous metals price shocks and emphatically analyse the time-varying effect of the financialization of nonferrous metals markets on China's industrial sector via the monthly data of copper from August 2006 to December 2016. The results show that financialization of the copper market on China's industrial sector output and price are mostly negative over time. The increase in copper price driven by the financialization of the copper market is the most important cause of the reduction in China's industrial sector output. However, the impact of the financialization of the copper market on China's industrial sector price is relatively small, compared to the impact on China's industrial sector output. In addition, the impact of the financialization of the copper market on China's industrial sector has increased after the international financial crisis.

An Empirical Analysis of the Impact of Foreign Direct Investment and Industrial Sector Performance on Nigerian Economy

This research investigated the impact of foreign direct investment and industrial sector performance on Nigeria economy using time series annual data from 1981 – 2015. The study explores dynamics amongst the variables within the Vector Error Correction Model (VECM). The Augmented Dickey Fuller (ADF) and Philip Perron’s (PP) test reveals that all variables contained a unit root and were integrated of order one I(1). The Johansen Cointegration test result reveals the presence of a long-run relationship between FDI, Industrial Sector Output and GDP. Furthermore, VECM estimate shows that FDI and industrial sector output had a slight significant positive impact on GDP.The study concludes that Nigeria is yet to fully reap the benefit of FDI since its contribution to GDP is still very low at the moment, whilst the contribution of the industrial sector in the country has not been vibrant enough to spur economic growth in Nigeria. The study therefore recommends among other things that social and economic infrastructure be improved as this will help lessen the burden of industrialist and eventually lower the cost of doing business and in turn attract FDI inflow into Nigeria. Keywords : Industrial Sector, Dynamics, Cointegration, Inflow, Economy DOI : 10.7176/EJBM/11-11-08 Publication date : April 30 th 2019

Foreign Direct Investment Inflows And Real Sector: A Vector Autoregressive (Var) Approach For The Nigerian Economy

The flows of foreign direct investment (FDI) to developing economies have been considered important for sustainable growth as they enhance job creation and the transfer of technology and management expertise. As a result, the attention of scholars has been drawn to examining the relationship between FDI and growth resulting in several studies in this area. Notwithstanding, few studies have been carried out on the impact of FDI on real sector growth, particularly in the Nigerian economy. Hence, this study examines the effect of FDI on the real sector in Nigeria between the periods 1981–2016 using the impulse response function (IRF) and variance decomposition (VDC) of VAR. The study found that agricultural sector output responded positively to shocks in FDI inflows but it was statistically insignificant. The IRF also revealed that industrial sector output responded positively to shocks in FDI and it was statistically significant. This presupposes that the inflows of foreign direct investment have positive effects on the growth of the industrial sector in Nigeria. The VDC showed that FDI inflows exert influence on both the agricultural sector output and industrial output. However, FDI inflows influence the industrial sector output in a greater proportion than the agricultural sector. Using the VAR Granger causality, the study also found that while FDI inflows cause growth in industrial sector output, they, however, do not cause growth in agricultural sector output. The implication of the study is hinged on the fact that FDI inflows have not been driving the growth of the agricultural sector in Nigeria. This could be adduced to some structural bottlenecks besetting the growth and competitiveness of the sector, which have made the sector unattractive to foreign investors. The study, therefore, recommends that the government should greatly invest in rural infrastructure development that will encourage foreign investment. Also, the government should intensify research and development institutions in order to seek new knowledge and enhance innovation in the agricultural sector.

The Effect of Macroeconomic Variables on Industry Sector Output Growth of Ethiopia

Industrialization plays a key role in the process of a nation’s economic development. The experience of the developed world revealed that industrialization significantly increased their productivity and changed the economic structure. Mainly with the context of reoccurring unstable macroeconomic performance in Ethiopia, analyzing the effect of macroeconomic variables on industry sector output growth is a proper way to design suitable industrial policies. Therefore, this study aimed to examine the effect of some macro-economic variables on the industry output growth in Ethiopia. To do so the study used a time series data ranging from 1991 up to 2018 from Ministry of Finance and Economic Cooperation of Ethiopia. The study also used Augmented Dickey-Fuller (ADF) and the Phillip-Perron (PP) unit root tests of stationary, Auto Regressive Distributed Lag (ARDL) bound test to co-integration and error correction model. Accordingly the study confirmed the existence of a long-run relationship between industrial output growth and macroeconomic variables. Macroeconomic variables such as, lending rate, inflation rate and trade balance found to be affecting the industrial sector output growth negatively, positively and negatively, respectively in the long run. Therefore, the government has to keep lending rate to the level that could be amenable for firms and maintaining the trade balance; via manipulating the export and import.

Foreign Direct Investment and Industrial Sector Performance: Assessing the Long-Run Implication on Economic Growth in Nigeria

This paper aimed at examining the impact of Foreign Direct Investment (FDI) and Industrial Sector Performance on economic growth in Nigeria. This study utilized annual time series data for the period 1981-2015 using elaborate econometric analysis which tests the sensitivity of GDP to shocks in FDI and Industrial Sector Output, using the Impulse Response Functions (IRFs) and Variance Decomposition (VDC) techniques within a Vector Autoregressive (VAR) framework. The Johansen Cointegration test result reveals the absence of a long-run relationship between FDI, Industrial Sector Output and GDP. The result also shows the existence of a bidirectional relationship between FDI and Industrial Sector Output, GDP and Industrial Sector Output, with a unidirectional causality running from FDI to GDP. The VAR estimate shows that FDI had a slight significant positive impact on GDP, while Industrial Sector Output had a small significant positive impact on GDP at present, with a negative relationship observed at previous periods. The impulse response functions clearly reveal that GDP exhibited negative response to shocks in FDI up to the 3rd period, while the effect was positive from the 4th period henceforth, while GDP also exhibited a negative response to shocks in Industrial Sector Output throughout the period observed. The variance decomposition analysis further revealed that GDP was mainly driven by shocks in FDI, with industrial sector output contributing very little. The study concludes that Nigeria is yet to fully reap the benefit of FDI since its contribution to GDP is still very low at the moment, whilst the contribution of the industrial sectorin the country has not be vibrant enough to spur economic growth. The study therefore recommends among other things that social and economic infrastructure be improved as this will help lessen the burden of industrialist and eventually lower the cost of doing business and in turn attract FDI inflow into Nigeria.

An Empirical Study of Inter-Sectoral Linkages and Economic Growth in India

The objective of the present paper is to examine casual relationship between GDP, agricultural, industrial and service sector output in India using time series data from 1950-51 to 2011-12.The study conducts an econometric investigation by applying methodologies, viz., Stationary tests, and Johansen’s Cointegration test, Johansen’s Vector Error Correction Model (VECM) in VAR and Impulse Response Function and Variance Decomposition Analysis. With all the variables in log terms being I(1), Johansen’s co-integration test confirms two long run relationships among the variables at 5% significance level. It reveals that there exists bidirectional causality among the agriculture, industry, service sector and GDP and agriculture and industrial sector with services sector, while there is a unidirectional causality between agriculture and industry sector. However, results based on vector error correction model indicate a weak association between the sectors in the short run. Dynamic causality results show that contribution GDP forecast error by the services sector is the highest, followed by agriculture and industry sectors, while the contribution to the agriculture sector forecast error by GDP is the highest, followed by the service sector and industry. In the case of the industry sector, the explanatory power of one standard deviation innovation in the agriculture sector and the services sector to forecast error variance is quite high (33.38% and 5.38%). Further, results of decomposition variance analysis and impulse response suggest that the agriculture sector plays the main role in determining the overall growth rate of the economy through its linkages to other sector. The analysis of inter – sectoral linkages identify agriculture as the main economic activity that controls most economic activities in India.

Does Kaldor’s hypothesis hold in India?

Issues relating to the interaction between the industrial sector of an economy and the overall economic activity under Kaldor’s hypothesis have been an interesting area of research. While a number of empirical studies have been carried out to test Kaldor’s hypothesis in many industrial and emerging economies, a similar study in the Indian context is conspicuously absent. With a series of comprehensive economic reforms initiatives introduced in India during the last two decades, there has been greater market orientation in the overall economy, and the inter-linkages between the industrial sector and the overall economy have assumed new dimensions. Against this backdrop, the present study empirically examines Kaldor’s hypothesis in the Indian context. For the empirical investigation, various time series econometric techniques such as Johansen and Juselius co-integration test and Granger causality test are applied to examine the relationship between industrial output and overall economic growth measured in terms of Gross National Product. The co-integration analysis takes into account the non-stationarity problem in the data, which is generally observed in various macroeconomic time series. It examines the presence of long-term stability in the relationship between two or more time series when they are integrated of order 1. The associated error correction mechanism explores the short term dynamics along with the adjustment process. We have used Indian annual data covering the period 1970-2011 for the empirical exercises. From the estimated results, it was revealed that both our time series under investigation, viz ., industrial sector output and overall GNP were non-stationary and integrated of order 1. But the Johansen-Juselius co-integration test established long-term stability in their association. The error-correction mechanism revealed that any short-term discrepancy in the relationship was corrected over time. The results also showed a unidirectional causality running from economic growth to growth in industrial sector. Thus, GNP-led industrial growth pattern exists in India, and our findings fail to provide evidence supporting Kaldor’s hypothesis in the context of fast-growing Indian economy. The findings of the present study have important policy implications. Given the fact that the industrial sector is the backbone of the overall economy, it needs to grow consistently. Particularly, the policy makers in India should strive to promote India’s manufacturing exports along with the service sector.

Information flow within the West African innovation systems

We used mutual information and transmission power as indicators of knowledge circulation between innovation actors. The units of analysis in scientific publications are indexed in the Web of Science with at least one West African-based address. We found that at the regional level, the university is the biggest knowledge producer followed by the government and industry in that order; however, at the national level, the government is the biggest information producer in majority of countries. The industrial sector output is weak both at the regional level and individual country level. It is even null in some countries. Mutual information indicated the existence of synergy between the three actors, both at the regional and national levels. However, its value is too low to allow for knowledge circulating fluently among actors.

Does Financial Development Cause Economic Growth? The Case of India

This article examines whether financial development has ‘caused’ economic growth in India since 1996. The dynamic interactions between the growth of real Gross Domestic Product and indicators of financial development are investigated using the concept of Granger Causality after testing for cointegration using both the Engle-Granger and Johansen techniques. The ADF test for cointegration proposed by Gregory and Hansen (1996) reveals that there has been both the level shift and regime shift in the specifications relating economic growth and financial development. The empirical results obtained by the Johansen method and ADF test suggest the existence of a stable long-run relationship between stock market capitalization, bank credit and growth rate of real GDP. The growth rate of real GDP is also found to be cointegrated with financial depth. However, causality runs from the growth rate of real GDP to stock market capitalization. The sector-wise rates of growth of the industrial and services sectors are found to be cointegrated with the stock market development as well as banking sector development and financial depth. The direction of causality for both the sectors runs from the rate of growth to stock market capitalization. We also observe that financial depth causes industrial growth and causality runs in both directions between bank credit and industrial growth. Furthermore, volatility in stock prices is cointegrated with each growth rate—of GDP, of industrial sector output and of the service sector output. The article establishes that, in an overall sense, economic growth has ‘caused’ financial development in India.

Industrial output restriction and the Kyoto protocol: An input–output approach with application to Canada

The objective of this paper is to assess the economic impacts of reducing greenhouse gas emissions by decreasing industrial output in Canada to a level that will meet the target set out in the Kyoto Protocol. The study uses an ecological–economic Input–Output model combining economic components valued in monetary terms with ecologic components – GHG emissions – expressed in physical terms. Economic and greenhouse gas emissions data for Canada are computed in the same sectoral disaggregation. Three policy scenarios are considered: the first one uses the direct emission coefficients to allocate the reduction in industrial output, while the other two use the direct plus indirect emission coefficients. In the first two scenarios, the reduction in industrial sector output is allocated uniformly across sectors while it is allocated to the 12 largest emitting industries in the last one. The estimated impacts indicate that the results vary with the different allocation methods. The third policy scenario, allocation to the 12 largest emitting sectors, is the most cost effective of the three as the impacts of the Kyoto Protocol reduces Gross Domestic Product by 3.1% compared to 24% and 8.1% in the first two scenarios. Computed economic costs should be considered as upper-bounds because the model assumes immediate adjustment to the Kyoto Protocol and because flexibility mechanisms are not incorporated. The resulting upper-bound impact of the third scenario may seem to contradict those who claim that the Kyoto Protocol would place an unbearable burden on the Canadian economy.

The Largest Companies in European Union and Turkey of General Concentration Levels and Performance lndicators

As a result ol industrializarion, output composition has changed and large scale units of production have appeared. In industrial sector output have began to be collected under the few number of large-scale and strong corporations. With the influence of the globalization national corporations have opened to the foreign market. They came across especially with the largest corporations in the European Union. Freedom in the trade increases the foreign competition and decreases the profitability. Decreasing in profitability increase the concentration in the market by making some of the corporations resigned fi\'om the market. High level of concentration influences the performance indicators such as value added, profitability, productivity, and employment of the corporations. The purpose of this study is to compare the general concentration levels, value added and performance indicators ol the largest 500 industrial corporations in the European Union and Turkey, during the Customs Union process between Turkey and European Union started in 1996 In this respect, first of all, market structure and performance indicators have been defined, then the largest companies in European Union and Turkey of general, sectoral and company scales concentration levels and performance indicators have been compared each other.

Industrial energy use in Ontario from 1962 to 1984

Both the magnitude and pattern of energy use in the Ontario industrial sector have changed significantly over the 1962–1984 period. In order to gain greater insight, a Divisia index approach was used to disaggregate changes in the aggregate energy intensity of the Ontario industrial sector into structural and intensity components, the first component measuring changes due to shifts in the composition of industrial sector output, the second measuring changes due to energy intensity shifts of individual industries. Of particular interest were changes between the pre-oil-shock period (1962–73) and post-oil-shock period (1973–84), as well as differences in the trends of fossil fuel and electricity use. Structural changes were found to be of little importance in the 1962–73 period, but of substantial importance in the 1973–1984 period in reducing the aggregate energy intensity of the Ontario industrial sector. Changes in the intensity of individual industries, on the other hand, were found to be significant in the earlier period but of lesser importance in the later period.