Sector GDP Research Articles

Profitability determinants of Nepalese commercial banks

Purpose- The purpose of this study is to examine the the key determinants of profitability of Nepalese commercial banks. Methodology- This study employs descriptive statistics to describe the profitability of Nepalese banks and its determinants. Further, the degree of correlation among different indicators of profitability and its determinants has been assessed by calculating correlation coefficient. Finally, this study has adopted a panel data regression model (Fixed Effect Model and Random Effect Model) to investigate the determinants and their impact on profitability of Nepalese commercial banks. Findings- The analysis reveals that the bank pofitability measured by ROA of Nepalese commercial banks is significantly affected by concentration ratio, banking sector development, GDP growth, inflation and exchange rate significantly in opposite direction rather it is not significantly affected by the internal factors like bank size, capital base, deposit, loan, off-balance sheet activities and number of branches. Another indicator of bank profitability; NIM is significantly affected only by capital adequacy, absolute number of branches and inflation rate. Conclusion- This study concluded that the profitability of Nepalese commercial banks measured by return on assets is significantly influenced by the external factors. Among external factors, industry specific factors have high degree of impact on return on assets whereas macroeconomic variables have quite a weak degree but significant impact on profitability of Nepalese commercial banks as measured by return on assets. Further, the profitability measured by net interest margin (NIM) is significantly influenced only by capital adequacy, absolute number of branches and annual inflation rate.

Analyzing the role of industrial sector's electricity consumption, prices, and GDP: A modified empirical evidence from Pakistan

Electricity usage plays a vital role in raising the massive growth in the economy; also, the industrial sector is the key factor of overall energy demand closely related to the economy. The study aims to contribute in two ways. First, the Vector Error Correction Model (VECM) estimates electricity consumption in Pakistan during 1970-2018 to find the relationship between electricity consumption, price, and real gross domestic product. Second, decomposing the overall impact of an unexpected shock on each variableos Dynamic Variance Decomposition Technique applied. The empirical analysis shows that the factors are co-integrated. The results also indicate the long-run relationship between electricity consumption, price, and real gross domestic product in the industrial sector. Further, the VECM analysis responses are also confirmed by the variance decomposition method. The findings confirm the potential of the industrial sector. We propose that formalized and proper assurance of electricity needs and demands at a reasonable price can boost the local industry's confidence and attract foreign investors. However, a strong governance structure should be extended to the public sector to ensure policies that priorities the distribution of energy to businesses for development.

THE CRITIQUE OF MADDISON’S METHOD OF REVISING CHINA’S GDP DATA

Economist Angus Maddison is famous for his exploring the revision of economic statistical data, including China’s GDP data since the 1990s. This is a useful work. Maddison has revised China's GDP data from multiple angles, including the revision of China's non-material service sector GDP data. Maddison assumed that the non-material service sector in China has had a zero scientific and technological progress rate since the 1990s, while based on the data from the National Bureau of Statistics of China, the rate of scientific and technological progress in the non-material service sector should be big. Maddison's assumptions have led to a significant reduction in China's GDP data, and thus China's economic growth rate has dropped significantly. This paper argues that the high-tech progress rate of the non-material service sector-led and promoted by information technology is not only possible but also very likely, so China’s GDP data is credible in general, and of course, some small deviations and inaccuracies existed in China statistical GDP is understandable and acceptable.

Forecasting Carbon Emissions with Dynamic Model Averaging Approach: Time-Varying Evidence from China

Although energy-related factors, such as energy intensity and energy consumption, are well recognized as major drivers of carbon dioxide emission in China, little is known about the time-varying impacts of other macrolevel nonenergy factors on carbon emission, especially those from macroeconomic, financial, household, and technology progress indicators in China. This paper contributes to the literature by investigating the time-varying predictive ability of 15 macrolevel indicators for China’s carbon dioxide emission from 1982 to 2017 with a dynamic model averaging (DMA) method. The empirical results show that, firstly, the explanatory power of each nonenergy predictor changes significantly with time and no predictor has a stable positive/negative impact on China’s carbon emissions throughout the whole sample period. Secondly, all these predictors present a distinct predictive ability for carbon emission in China. The proportion of industry production in GDP (IP) shows the greatest predictive power, while the proportion of FDI in GDP has the smallest forecasting ability. Interestingly, those Chinese household features, such as Engel’s coefficient and household savings rate, play very important roles in the prediction of China’s carbon emission. In addition, we find that IP are losing its predictive power in recent years, while the proportion of value-added of the service sector in GDP presents not only a leading forecasting weight, but a continuous increasing prediction power in recent years. Finally, the dynamic model averaging (DMA) method can produce the most accurate forecasts of carbon emission in China compared to other commonly used forecasting methods.

Early estimates of the impact of the COVID-19 pandemic on GDP: a case study of Saudi Arabia

ABSTRACT The COVID-19 pandemic has affected economic sectors in a very heterogeneous way. In the early stages of the economic lockdown, only limited economic data, if any, related to the event were available. With the government’s discretionary measures to contain the infection, it became obvious that some sectors will suffer more than others. We have used this information within the input-output framework to calibrate demand shocks to individual sectors and to obtain early estimates of the impact on sectoral and overall GDP. Given the high level of uncertainty, we designed three scenarios, reflecting the severity of the shock, its sectoral distribution, and the time needed for recovery, and applied to the Saudi economy. The negative impact on headline GDP in 2020 is estimated to range from −4.8% to −9.8% compared to the baseline level, while the government’s fiscal countermeasures result in a positive effect of some 2.5% in real GDP. The study also shows how to accommodate a qualitative shift in economic conditions given the still-evolving pandemic. We consider the potential situation of a second wave of the infection that would enforce a protracted lockdown and imply second-round effects.

Effect of the Quality of Institutions on Fiscal Pressure in the Countries of the West African Economic and Monetary Union (WAEMU): Evidenced by Informal Sector Channel

This paper aims to analyze the effects of the quality of institutions on the total tax burden through the informal sector in WAEMU countries over the period 1996-2015. The estimation of the parameters by GMPs shows that the improvement in the quality of the institutional environment reduces the size of the informal sector and this reduction in the size of the informal sector in turn leads to an increase in the tax burden rate. It also shows that the level of development and trade openness improve the total tax burden of WAEMU countries, while inflation, the share of agriculture and the informal sector in GDP reduce the total tax burden. As for the share of natural resources in GDP, its effect on fiscal pressure is ambiguous because it varies according to the indicator used to measure the quality of institutions in the regression. Keywords : Tax pressure, Informal sector, Institutions, WAEMU DOI: 10.7176/JESD/11-20-12 Publication date: October 31 st 2020

Why did make in India scheme fail to attract FDI inflows in Indian manufacturing sector?

To boost the manufacturing sector, India announced a highly ambitious scheme Make in India in 2014. The scheme aims to transform India into a global design and manufacturing hub by fostering innovation, facilitate investment and build best in class manufacturing infrastructure. The scheme envisioned to increase the share of the manufacturing sector to the GDP to 25% and create 100 million new jobs by 2025. Another prime objective of the plan was to attract foreign direct investment in the Indian manufacturing sector. The government identified 25 industries in the manufacturing sector. Several steps were undertaken to publicise the campaign both domestically and internationally. The government allocated around Rs. 1821.5 Cr since the launch of the scheme. But, after the six years of its launch, the scheme has made little impact on the economy. The scheme could neither increase the share of the manufacturing sector in GDP nor could attract any significant volume of FDI in the manufacturing sector. In this backdrop, this study attempts to assess the performance of the scheme. The paper also attempts to investigate the factors that hindered its success.

Sectoral Digital Intensity and GDP Growth After a Large Employment Shock: A Simple Extrapolation Exercise

We examine the dynamics of GDP following an economy-wide pandemic shock that curtails physical mobility and the ability to perform certain tasks at work. We examine whether greater reliance on digital technologies has the potential to mediate employment and productivity losses. We employ industry-level indices of task-based digital intensity and ability to work from home (home-shorability''), in conjunction with publicly available data on employment and GDP for Canada, and document that: (i) employment responses after the onset of the shock are milder in digitally-intensive sectors; (ii) conditional on the size of employment changes, GDP responses are less extreme in IT-intensive sectors. We suggest a simple state-dependent algorithm for predicting output dynamics as a function of employment across industries and locations with different digital intensity. In our baseline scenario, aggregate output returns to pre-crisis levels eight quarters after the initial shock onset, although we find significant heterogeneity in recovery patterns across sectors.

The Impact of Industry 4.0 on Changes in the Sectoral Structures of the Economies and Equity Markets within the Selected EU Countries

The last two decades in the world are associated with the phenomenon of the Internet economy and with the emergence of new technologies that bring significant productivity gains for the economy. At the same time, restructuring processes have started, affecting changes in the sectoral GDP structure as well as changes in the sectoral composition of stock indices. The purpose of this article is to specify in more detail the relationship between the real economy and the stock market in terms of the onset of the 4th industrial revolution within the EU. The focus of our research is primarily on larger EU economies with a functioning stock market. In addition, the article also provides a detailed analysis of the structure of selected stock indices in terms of representation of the individual sectors, while only the German market seems relevant for further research. And it is on the German market that there is a statistically significant relationship between the development of the stock index DAX and German GDP. However, specifics affecting the development of the European market in comparison with the development of the US economy are also formulated.

Sectoral Growth and Income Inequality in ASEAN-5 Countries: Case of Low-Middle Income Economies

This paper aims to explore the relationship between growth in economic sectors, especially manufacturing, service, and agriculture, towards income inequality. Furthermore, it utilizes panel data for low-middle income ASEAN countries. The result shows that the share of agricultural sector in GDP has a significant and negative relationship with income inequality. In fact, the effect is robust for the incorporation of control variables. Therefore, it underlines the importance of agricultural sector development for reducing inequality and also for fostering ASEAN economic integration.

Drivers of CO2-Emissions in Fossil Fuel Abundant Settings: (Pooled) Mean Group and Nonparametric Panel Analyses

The present inquiry addresses the income-environment relationship in oil-producing countries and scrutinizes the further drivers of atmospheric pollution in the respective settings. The existing literature that tests the environmental Kuznets curve hypothesis within the framework of the black-box approaches provides only a bird’s-eye perspective on the long-run income-environment relationship. The aspiration behind this study is making the first step toward the disentanglement of the sources of carbon dioxide emissions, which could be employed in the pollution mitigation policies of this group of countries. Based on the combination of two strands of literature, the environmental Kuznets curve conjecture and the resource curse, the paper at hand proposes an augmented theoretical framework of this inquiry. To approach the research questions empirically, the study employs advanced panel cointegration techniques. To avoid econometric misspecification, the study also employs for the first time a nonparametric time-varying coefficient panel data estimator with fixed effects (NPFE) for the dataset of 37 oil-producing countries in the time interval spanning between 1989 and 2019. The empirical analysis identifies the level of per capita income, the magnitude of oil rents, the share of fossil fuel-based electricity generation in the energy mix, and the share of the manufacturing sector in GDP as essential drivers of carbon dioxide emissions in the oil-rich countries. Tertiarization, on the contrary, leads to a substantial reduction of emissions. Another striking result of this study is that level of political rights and civil liberties are negatively associated with per capita carbon emissions in this group of countries. Furthermore, the study decisively rejects an inverted U-shaped income-emission relationship and validates the monotonically or exponentially increasing impact of average income on carbon dioxide emissions.

The nexus of economic growth, priority sector lending and non-performing assets: case of Indian banking sector

PurposeIn recent years, the Indian banking sector is facing a major cause of concern in the form of Nonperforming Assets (NPA), and the priority sector lending (PSL) is generally recognized as the major factor contributing to it. Thus, the present study has been carried out with the objective of examining the relationship between priority sector lending and GDP growth. Thereafter, the role of PSL and certain other bank-specific, industry-specific and macroeconomic variables in determining NPA has been studied.Design/methodology/approachTaking a sample of 45 scheduled commercial banks, the study has been carried out for 14 years (2004–2018). Granger causality between PSL and GDP has been examined by applying the Dumitrescu-Hurlin test. For the purpose of investigating the impact of PSL and other determinants on NPA, both static and dynamic panel regression have been performed. Under the dynamic panel, system generalized methods of moments (S-GMM) approach has been followed.FindingsThe findings show that there exists a positive correlation and bidirectional causal relationship between PSL and GDP, which implies that PSL brings additional growth for the whole economy. In addition to it, PSL is found to be insignificant for the NPA ratio, and thus, it can be inferred that credit extended to government-specified sectors does not bring any major increase in the bad loan portfolio of banks.Practical implicationsThe policymakers and bank management can take a cue from the findings of this study to decrease the exposure to loan nonrepayment issue. The priority sectors are in need of formal credit for their growth, and since the rising population of the country can find employment in these sectors, banks should meet their credit needs while securing their position with regard to the NPA problem.Originality/valueThe issue of NPA determinants, and in particular, the contribution of priority sector lending in it has not been much explored for Indian banking sector. Also, the present study adds to the literature by using the causality approach for examining the importance of directed credit schemes for economic growth.

Long-term assessment of groundwater resources carrying capacity using GRACE data and Budyko model

Groundwater is crucial for the economic development in arid and semi-arid areas. However, groundwater resources have been over-exploited for meeting the increasing demands in agriculture, industry and domestic use. Therefore, the capacity of groundwater resources for supporting the economic development has been indeed reduced, which made a challenge for the assessment of the groundwater resources carrying capacity (GRCC). The present study constructed a new GRCC index (D) for assessing the long-term GRCC variation in Zhangjiakou of Hebei Province, China (ZJK) using Budyko equation, Gravity Recovery and Climate Experiment data (GRACE), Global Land Data Assimilation System data (GLDAS), sector water consumption data and GDP data. Our results shows that the short-term (2002–2017) annual and monthly anomalies in terrestrial water storage (TWSA) and groundwater storage appeared to be decreased, the anomalies in soil moisture storage tend to be zero while anomalies in snow water tend to be increased with annual rate of 2 cm year−1. The Budyko-derived long-term (1948–2018) groundwater storage changes (GWC) has declined from −310.9 to −455.6 cm and the large number of constructed wells for irrigation has accelerated the decline of groundwater resources in ZJK. Our results also shows the time series of D in ZJK were < 30%, 30% < D < 50% and D ≥ 50% during 1948–1988, 1990–1993 and 1994–2018, indicating that the degree of groundwater resources exploitation were in the state of no overload, overload and heavy overload, respectively. The contribution of groundwater resources for the economic development has exceeded 50%, which indicated that the economic development of ZJK depend much more on groundwater resources. Improving the water use efficiency cannot improve groundwater resources carrying capacity, however, reducing the absolute use of groundwater resources should be the effective way to alleviate the shortage of groundwater resources and improve groundwater resources carrying capacity.

What influences bank lending in Saudi Arabia?

PurposeDeterminants of credit growth in Saudi Arabia are investigated.Design/methodology/approachA panel approach is applied to macroeconomic and bank-level data spanning 2000 ‐15.FindingsBank lending is supported by strong bank balance sheet conditions (high capital ratio, and growth of NPL provisioning and deposits), and higher growth of both oil prices and non-oil private sector GDP. Lower bank concentration also helps, likely through greater competition, so does stronger institution. Consistent with the literature, lending by Islamic banks may be more responsive to economic activity. Lending remained robust in 2015 despite oil prices having declined, helped by strong bank balance sheets and as banks reduced their holdings of “excess liquidity”. To support bank lending in the period ahead, bank balance sheets need to remain strong. Fiscal adjustment and a reduced reliance on banks to finance the budget deficit would support credit provision to the private sector.Originality/valueThe paper is first to analyze in detail determinants of bank lending in Saudi Arabia applying a panel approach to bank level data, and draws critical policy implications.

ANALISIS DAMPAK SEKTOR INDUSTRI MANUFAKTUR, KEMISKINAN DAN BELANJA PEMERINTAH BIDANG LINGKUNGAN TERHADAP KUALITAS AIR DI INDONESIA

Manufacturing sector is one of the sectors that contribute to economic growth in Indonesia. Results of these contributions is the changing structure of the Indonesian economy from agriculture to the industrial sector. And poverty in Indonesia which is one indicator of well‐being in an area tend to be in 2000 to 2010 has a pattern that tends to decline, although not very significant. Of 2 (two) variables, namely the Manufacturing Sector and Poverty, the author tries to determine the impact of variables on water quality in Indonesia, by adding variable Expenditures Environmental Affairs as variables that also impact the water quality in Indonesia. Manufacturing Sector GDP, the number of poor, Regional Budget (APBD) Environmental Field, each is used as a proxy for the manufacturing sector, poverty and Environment Sector Government expenditure. The data is compiled based on 28 provinces in Indonesia in 2009, 2010 and 2011. The results obtained showed that the industrial sector and poverty have a negative impact on water quality while Government Expenditure Environment Sector positive effect on water quality in Indonesia.

DEVELOPMENTS IN THE HOUSEHOLD DEBT-TO-GDP RATIO ACROSS THE OECD COUNTRIES SINCE THE GLOBAL FINANCIAL CRISIS

The paper aims to investigate the developments in the household debt-to-GDP ratio across OECD countries over the period 2007–2017 from the standpoint of the individual tendencies in the numerator (household debt) and denominator (GDP) of the ratio, and to identify the groups of countries exhibiting similar patterns in the post-crisis evolution of these variables. The investigation employs a comparative analysis of the average rates of change in household debt and GDP in the sample, as well as k-medians clustering aimed at identifying similarities. The results of the research reveal significant disparities in the development of the household debt-to-GDP ratio across the examined countries in the analysed period driven by the dominant tendencies in its numerator and denominator, which in turn appear to be related to the pre-crisis levels of household sector indebtedness and GDP per capita, as well as the depth of recession that affected each of the particular economies.

LABOUR PRODUCTIVITY GROWTH IN THE LONG RUN: JAPAN, 1600–1909

This article examines long‐term labour productivity change in Japan from the early seventeenth century to the nineteenth century. We constructed sectoral labour force estimates based on the methodology presented in a previous study, who provided a sectoral GDP series covering the Tokugawa period. Our results show the industrial structure in the Tokugawa period remained relatively stable in comparison with the economy after the Meiji Restoration. Nevertheless, the estimates of sectoral labour productivity suggest expansion of the market economy in Tokugawa Japan influenced the development of industrialisation after the Meiji Restoration.

An Overview of Livestock and Dairy sector: Strategies for Its Growth in Eastern Indian State of Bihar

Livestock is a vital component of Indian economy in general and of agricultural sector in particular. In rural India over 15–20% families are landless and about 80% of the land holders belong to small and marginal farm size groups, livestock provides livelihood to two-third of the rural population. Livestock sector provides employment to about 8.8% Indian population. Contribution of livestock sector in GDP was 4.11% and it contributed 25.6% to the Agricultural GDP during 2018-2019. Livestock production constitutes an important component of Agricultural economy in Bihar as it assists in supply of food and nutrition, enhancement of income, livelihood and diversification of agricultural activities. Meanwhile, the livestock sub-sector contributed about 27% to the agricultural GSDP and 5% to state income or GSDP in 2012. Bihar has made great progress in dairy and is recognized for its high milk production from cows, buffalo and goats. Bihar’s milk production increased to 92.41 lakh tonnes in 2017-18 from 71.97 lakh tonnes in 2013-14, indicating an annual growth rate of 6.33%, during the five-year period. Productivity of milk per lactating cattle was found comparatively low as compared to others states Like Punjab, Gujarat, UP and MP. Contribution of livestock share in GVOA was found 25.4% in TE-2002-03 and increased to 31% in TE-2013-14 in Bihar whereas, the all-India share of livestock in GVOA stood at 26% in TE 2013-14. The share of meat in the total value of output from livestock sector has declined while that of milk has increased. The share of milk in GVOA has increased from 14% to 23% between TE-2003-04 and TE-2013-14, while at the all-India level; the share of milk in GVOA remained at 17% during the same period. Bihar has immense potential in livestock and dairy sector. If harnessed properly by suitable policy initiatives could be helpful in augmenting income, generating employment and providing nutritional security to state in particular and nation in general.

The Environmental Kuznets Curve: Industrial Application For Forecasting Waste Generation And Emissions Of Harmful Substances

Purpose. To determine sustainable development conditions according to the criteria of emissions of harmful substances and waste generation when modelling impact factors of the parameters and general environmental situation in Ukraine. Methods. In the research general scientific (analysis and synthesis, induction and deduction, analytical grouping) and special (abstraction, modelling, etc.) methods of studying economic phenomena and processes have been used. Results. For modelling of national sustainable development parameters by the parameters of emissions of harmful substances and waste generation it has been proposed to apply sectoral approach and the model of the environmental Kuznets curve (EKC). It has been proved that the EKC model should be used not only to model parameters of emissions of harmful substances, but also for waste generation. Besides, it has been proved that it is necessary to take into account not only national level indicators, but also the contribution of the leading sectors driving national economy. Modelling has been carried out for the following industries: processing; mining and quarry development; agriculture, forestry and fisheries; supply of electricity, gas, steam and conditioned air; transport, warehousing, post and courier services. The models are based on correlation between GDP, average nominal income per capita, environmental costs, waste generation and emissions of harmful substances at the national level and by its leading industries. It has been determined that reaching the "turning point" on sectoral EKCs correlates waste generation and emissions with industry`s rate of remuneration, value added (sectoral GDP) and sectoral investment in environmental protection in the context of industry`s specifics. It has been demonstrated that in Ukraine the "turning point" on the EKC has been provided by 20% of economically active population in industries that generate 46% of emissions amid country's average nominal income per employee and steady growth of environmental expenses for at least two years. Conclusions. It has been proved that the EKC for Ukraine should be analyzed by the sectors of national economy. To form effective national environmental policy, sectoral EKCs should be applied to determine emissions of harmful substances and waste generation. It has been determined that the key factor to ensure country`s sustainable development is environmental investment both at the national level and by its driving economic sectors. Thus, the sectoral EKC reflects the progress towards industries` sustainable development that form main revenue receipts of the government and determine the rate of remuneration in the real sector. Modelling of the EKC parameters for waste and emissions of harmful substances fully corresponds to the trends of sustainable economic growth and its transition to the innovative type of development.

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.