scholarly journals Electricity Demand in Pakistan: A Household Analysis

2019 ◽  
Vol 1 (2) ◽  
pp. 34-39
Author(s):  
Nauman Ahmed ◽  
Uzma Nisar
Keyword(s):  
Urban Areas ◽  
Positive Impact ◽  
Least Square ◽  
Economic Determinants ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Time Period ◽  
Increasing Demand ◽  
Residential Demand ◽  
Household Analysis

Availability of electricity is essential in modern age because it becomes a necessity of life. The present study used some economic and non-economic determinants that affect household demand for electricity. This study used PSLM survey data for the year 2013-14. The amount of electricity consumed by household was used as dependent variable whereas electricity price, household income, appliances, heating days, region, awareness, and rooms were taken as explanatory variables. Ordinary least square technique (OLS) was used for analysis. The findings of the study showed that Economic and demographic factors are important in determining electricity expenditure. In micro level analysis prices has strong and positive effect on electricity expenditures and it didn’t represent traditional behavior of demand with price. Price and income had positive impact during the period of study with demand for electricity. Expenditure on electricity is fairly higher during summer season. Positive and significant effect is estimated for stock of electricity appliances. Household members have significant effect on electricity expenditure but shows very smaller influence. The dummy variable for region indicates that electricity expenditure is higher for those households who are living in urban areas as compared to rural. Over the time period residential demand of electricity is increasing in Pakistan. As Pakistan is consumption oriented society and demand for appliances is increasing so government should take necessary measures to shift appliances on other resources other than electricity. Increasing use of the appliances increases demand for electricity therefore generation of electricity resources should be increased to meet this increasing demand.

scholarly journals Performance and Obstacles of SMEs: An Empirical Evidence from BRICS Countries

2019 ◽  
Vol 1 (2) ◽  
pp. 113-132
Author(s):  
Madiha Noshad ◽  
Mariam Amjad ◽  
Muhammad Nouman Shafiq ◽  
Seemab Gillani
Keyword(s):  
Positive Impact ◽  
Empirical Evaluation ◽  
Least Square ◽  
Firm Characteristics ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Brics Countries ◽  
Global Factor ◽  
Time Period ◽  
And Performance

This study empirically examines the performance and obstacles of SMEs in BRICS economies. For empirical evaluation, Ordinary Least Square technique has applied by taking the time period between “2000-2017”. Performance has taken as dependent variable and obstacles; firm characteristics and global factor have taken as explanatory variables. Estimated results show that ownership and size have a positive impact on SMEs growth and performance. Age has a negative and significant impact on the performance and growth of SMEs. Technology has a positive and significant impact on the performance of SMEs. Obstacles i.e. courts, crime, access to finance, practices of competitors and electricity has a negative and significant impact on the performance of SMEs. Access to land, infrastructure and workforce has a positive and significant impact on SMEs performance.  It becomes very important for the policymakers or investigators to pay attention towards making SMEs more competent, capable and productive in order to attain the goal of sustainable development and progress.

Foreign direct investment and economic growth nexus in Africa

2019 ◽  
Vol 11 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Edmond Hagan ◽  
Anthony Amoah
Keyword(s):  
Economic Growth ◽  
Financial Market ◽  
Positive Impact ◽  
Least Square ◽  
African Countries ◽  
Data Set ◽  
Content Type ◽  
Ordinary Least Square ◽  
Variable Approach ◽  
Time Period

Purpose African countries are generally fragile. This and other related characteristics affect the potential for growth and development. The purpose of this paper is to investigate whether the effect of FDI on economic growth is contingent on a financial system that accounts for financial market fragility. An important point of departure from earlier studies is the adoption of a new measure of financial market fragility. Design/methodology/approach Given the uniqueness of the data set, the study uses a panel data and estimates an econometric model using an instrumental variable approach. For robustness purposes, a pooled ordinary least square is also estimated. Findings The study provides evidence that if the financial market is fragile as in the case of Africa, FDI inflows may have a marginally significant positive impact on economic growth. The findings suggest that fragility in the financial market is a key absorptive capacity and cannot be trivialised when exploring FDI–growth nexus in Africa. Research limitations/implications The uniqueness of the data set limited the time period of the study. Nonetheless, the findings are still crucial to policy makers in Africa and other developing countries with similar characteristics. Originality/value To the best of the authors’ knowledge, this is the first study in Africa to investigate the FDI–growth nexus which accounts for financial market fragility.

scholarly journals Estimating a global demand model for soybean traffic through the Panama Canal

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Javier Ho ◽  
Paul Bernal
Keyword(s):  
Pacific Northwest ◽  
Least Square ◽  
Panama Canal ◽  
Demand Model ◽  
Department Of Agriculture ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Global Demand ◽  
Alternative Routes ◽  
The U.S

AbstractThis study attempts to fit a global demand model for soybean traffic through the Panama Canal using Ordinary Least Square. Most of the soybean cargo through the interoceanic waterway is loaded on the U.S. Gulf and East Coast ports -mainly destined to East Asia, especially China-, and represented about 34% of total Panama Canal grain traffic between fiscal years 2010–19. To estimate the global demand model for soybean traffic, we are considering explanatory variables such as effective toll rates through the Panama Canal, U.S. Gulf- Asia and U.S. Pacific Northwest- Asia freight rates, Baltic Dry Index, bunker costs, soybean export inspections from the U.S. Gulf and Pacific Northwest, U.S. Gulf soybean basis levels, Brazil’s soybean exports and average U.S. dollar index. As part of the research, we are pursuing the estimation of the toll rate elasticity of vessels transporting soybeans via the Panama Canal. Data come mostly from several U.S. Department of Agriculture sources, Brazil’s Secretariat of Foreign Trade (SECEX) and from Panama Canal transit information. Finally, after estimation of the global demand model for soybean traffic, we will discuss the implications for future soybean traffic through the waterway, evaluating alternative routes and sources for this trade.

scholarly journals The Factors Affecting Land Prices In Housing Location In Sidoarjo Regency

2017 ◽  
Vol 1 (1) ◽  
pp. 37-47
Author(s):  
Partomi Simangunsong ◽  
Arasy Alimudin ◽  
Muh. Barid Nizaruddin Wajdi
Keyword(s):  
Residential Location ◽  
Least Square ◽  
City Center ◽  
Sale Price ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Road Width ◽  
Log Linear ◽  
Road Distance

The need for residential location is one of the basic needs of the community and the attractiveness of the residential location is a unique feature where this feature is not made by the respective occupants, but by external factors from the residential environment in the area. This study aims to analyze the factors that are considered as the basis that affect the price of land. This research uses quantitative approach with associative research method. Linear analysis with quadratic method. Ordinary Least Square (OLS). From the analysis of this research model obtained log-linear F-accounting 70,162 while the value of F-table (0,05; 5,48) is 2,45. because F-count> F-table, Ho means rejected and explanatory variables include Distance to city center, Distance to main road, Distance to toll gate, Road width, and security simultaneously can be explained significantly at land sale price.

scholarly journals Determinants of Household Debt in Malaysia from the year 2010 to 2017

2019 ◽  
Vol 5 (2) ◽  
pp. 91
Author(s):  
Zahariah Mohd Zain ◽  
Nurul Ainun Ahmad Atory Ahmad Atory ◽  
Sarah Amirah Hanafi
Keyword(s):  
Positive Relationship ◽  
Negative Relationship ◽  
Housing Price ◽  
Least Square ◽  
Household Debt ◽  
Macroeconomic Variables ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Lending Rate

Household debt has become an issue in the Malaysian economy as it affects the country socially and economically.This study aims to examine the determinants of household debt from the year 2010 until 2017. This study employs the Ordinary Least Square (OLS) method and the macroeconomic variables used in this study are Gross Domestic Product (GDP), base lending rate, unemployment and housing price as independent variables. The results indicate that the trend of household debt in Malaysia has shown a continuous rise from the year 2010 to 2017. GDP, base lending rate and housing price indicate a positive relationship towards household debt while unemployment shows a negative relationship to household debt in Malaysia. All explanatory variables have shown a significant relationship except for GDP. Housing price has been found to be the most significant factor and positively related to household debt. The findings indicate that the higher the price of houses, the higher the household debt will be.

scholarly journals ANALISIS DETERMINASI PERTUMBUHAN EKONOMI PROVINSI JAMBI

2018 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Ali Fahmi
Keyword(s):  
Economic Growth ◽  
Government Spending ◽  
Capital Investment ◽  
Time Series Data ◽  
Negative Impact ◽  
Positive Impact ◽  
Least Square ◽  
Series Data ◽  
Ordinary Least Square ◽  
Investment Capital

This research aims to analyze the effect of government spending, investment of foreign capital investment, capital investment In Land and labor against growth of Jambi province during the 2004-2015. This research using Time Series data with regression analysis "Ordinary Least Square (OLS) wear EViews 8.  The findings from this research indicate that Labor become the most variable gives a positive impact against the next economic growth, government spending and investment, while investing PMDN PMA gives negative impact on The Economic Growth Of The Province Of Jambi. PMA investment posit no impact and no signikan against economic growth this is not prevalent, but it is possible the investment PMA in Jambi province is relatively small and still no impact in the absorption of the local Workforce. Menyikapai is an effort to boost the Economic growth of the Province of Jambi then needed a special business development policies should be directed at the activities that are labor-intensive to absorb labor as much as possible. Keywords: economic growth, government spending, PMA, the PMDN, and labor.

What Are the Leading Bank-Specific and Macroeconomic Factors Influencing Islamic Bank Performance?

2021 ◽  
pp. 153-171
Author(s):  
Mosharrof Hosen
Keyword(s):  
Positive Impact ◽  
Least Square ◽  
Capital Adequacy ◽  
Islamic Banks ◽  
Cross Sectional ◽  
Macroeconomic Factors ◽  
Mena Countries ◽  
Ordinary Least Square ◽  
Islamic Bank ◽  
Asset Quality

Despite the proven sustainability and growth of Islamic banks during the financial crisis period, many scholars criticise the current performance of Islamic banks. Therefore, policymakers are continuously getting worried due to inconclusive finding of different research related to Islamic bank profitability. To shed the light of raising concern, this study investigates the issue from considering both macroeconomic and bank-specific factors. The annual cross-sectional data has been collected from 46 Islamic banks in 10 selected MENA countries over the period 2015-2019. The standardized pooled ordinary least square (OLS) approach's findings revealed that bank size, capital adequacy, GDP, and inflation have a significant positive impact on Islamic banks' return on asset, but asset quality has no significant effect on ROA. In contrast, most of the variables have an insignificant effect of ROE. Investors, financial analysts, and policymakers will get benefits from this study's results to secure their investment by successfully controlling the above-mentioned leading factors.

scholarly journals A Data-Driven Approach to Trip Generation Modeling for Urban Residents and Non-local Travelers

2020 ◽  
Vol 12 (18) ◽  
pp. 7688
Author(s):  
Fan Yang ◽  
Linchao Li ◽  
Fan Ding ◽  
Huachun Tan ◽  
Bin Ran
Keyword(s):  
Cellular Phone ◽  
Test Methods ◽  
Least Square ◽  
Data Driven ◽  
Urban Residents ◽  
Trip Generation ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Data Driven Approach ◽  
Non Local

Trip generation modeling is essential in transportation planning activities. Previous modeling methods that depend on traditional data collection methods are inefficient and expensive. This paper proposed a novel data-driven trip generation modeling method for urban residents and non-local travelers utilizing location-based social network (LBSN) data and cellular phone data and conducted a case study in Nanjing, China. First, the point of interest (POI) data of the LBSN were classified into various categories by the service type, then, four features of each category including the number of users, number of POIs, number of check-ins, and number of photos were aggregated by traffic analysis zones to be used as explanatory variables for the trip generation models. We used a random tree regression method to select the most important features as the model inputs, and the trip models were established based on the ordinary least square model. Then, an exploratory approach was used to test the performance of each combination of the variables with various test methods to identify the best model for residents’ and travelers’ trip generation functions. The results suggest land use compositions have significant impact on trip generations, and the trip generation patterns are different between urban residents and non-local travelers.

scholarly journals Panel FMOLS Model Analysis of the Effects of Livestock Support Policies on Sustainable Animal Presence in Turkey

2020 ◽  
Vol 12 (8) ◽  
pp. 3444
Author(s):  
Hilmi Erdal ◽  
Gülistan Erdal
Keyword(s):  
Cross Section ◽  
Educational Level ◽  
Least Square ◽  
The Other ◽  
Utilization Rate ◽  
Ordinary Least Square ◽  
Agricultural Income ◽  
Time Period ◽  
Presence Data ◽  
Animal Presence

This paper studied the effects of livestock support policies applied in Turkey. The effects of the support policies were built upon the change in the cattle presence data. Full Modified Ordinary Least Square (FMOLS) model was used in the analysis. In the panel dataset which was created for the study, the time period was taken as the years between 2004 and 2014 and the cross-section was 26 sub-regions. The results of panel FMOLS test for both the total livestock supports and each support component presents important details. According to the results of the analyses, a 1.0% increase in livestock supports leads to a 0.3% increase in animal presence in Turkey. On the other hand, it is stated that the utilization rate of the support payments is high in the western regions, whereas it is comparatively low in the eastern and interior regions in Turkey although the appliance of the policies is carried out in the same way, since animal presence in western regions in terms of fertile races is higher. This situation reveals the importance of breeders of high conscience, educational level, and agricultural income besides organized associations and provincial organizations.

scholarly journals Solving Multicollinearity Problem in Linear Regression Model: The Review Suggests New Idea of Partitioning and Extraction of the Explanatory Variables

2021 ◽  
Vol 2 (1) ◽  
pp. 12-20
Author(s):  
Kayode Ayinde, Olusegun O. Alabi ◽  
Ugochinyere Ihuoma Nwosu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Real Data ◽  
Least Square ◽  
Model Parameters ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Wide Range ◽  
High Level

Multicollinearity has remained a major problem in regression analysis and should be sustainably addressed. Problems associated with multicollinearity are worse when it occurs at high level among regressors. This review revealed that studies on the subject have focused on developing estimators regardless of effect of differences in levels of multicollinearity among regressors. Studies have considered single-estimator and combined-estimator approaches without sustainable solution to multicollinearity problems. The possible influence of partitioning the regressors according to multicollinearity levels and extracting from each group to develop estimators that will estimate the parameters of a linear regression model when multicollinearity occurs is a new econometrics idea and therefore requires attention. The results of new studies should be compared with existing methods namely principal components estimator, partial least squares estimator, ridge regression estimator and the ordinary least square estimators using wide range of criteria by ranking their performances at each level of multicollinearity parameter and sample size. Based on a recent clue in literature, it is possible to develop innovative estimator that will sustainably solve the problem of multicollinearity through partitioning and extraction of explanatory variables approaches and identify situations where the innovative estimator will produce most efficient result of the model parameters. The new estimator should be applied to real data and popularized for use.

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