Double-log Model Research Articles

Assessment of thermal and physicochemical properties of mechanic village soils derived from two different geological formations in Ogun State, Nigeria

This study assessed and compared selected soil properties, oil and grease content, and thermophysical parameters of sandy loam soils from two representative automobile mechanic village (MV) on two different geological formations in Ogun State, Nigeria. The two locations: Abeokuta and Sagamu are situated on a basement complex and Cretaceous-sedimentary formations, respectively. Ten sample points were established on each MV. Physico-chemical and in-situ thermal properties were measured using standard methods and KD2 Pro thermal analyzer, respectively. Three different regression models (linear, semi-log and double-log) were generated for the prediction of thermal conductivity ( λ s ) and specific heat capacity ( C s ). Topsoils in both MVs are slightly acidic to neutral, with an average oil and grease content > 100 mg/kg. Results of thermophysical parameters revealed that the average λ s values in MV soils of basement complex and sedimentary backgrounds were 1.656 and 1.988 W/mK, respectively. The average C s values in Abeokuta and Sagamu MV soils are 2.295 and 3.043 MJ/m3K, respectively. The regression analysis showed that the double log model performed better than both linear and semi log models for predicting λ s at both locations. All the tested regression models have good prediction effects on C s at location within cretaceous sedimentary, whereas linear and double-log models proved feasible for predicting C s at location underlain by basement complex.

ANALYSIS OF GROUNDWATER USE EFFICIENCY AND PRODUCTIVITY OF CROPS IN PAKISTAN: EVIDENCE FROM BALOCHISTAN PROVINCE

Balochistan is the largest province of Pakistan in terms of area, and most of its population depends on agriculture. It has an arid/semi-arid climate with frequent drought and dry spells. Almost half of the cultivated area is irrigated, and the primary source of irrigation is groundwater. Indus water available in Balochistan remains underutilized. Drought and tube well subsidy and other factors have resulted in over-exploited groundwater and unsustainable groundwater table. This situation affects agriculture, hence the livelihood of the residents. The study focused on analyzing the impact of using groundwater for irrigation on agricultural productivity and farmer’s livelihood in the Balochistan province of Pakistan. For this purpose, five villages were randomly selected from the district Quetta, where groundwater was the only source for irrigation. In each village, 20 farmers were interviewed through well-structured and pre-tested questionnaires. For each significant crop cultivated in the area, ‘Water Productivity’ was measured as Yield ⁄ Volume of water required in cubic meter/acre, ‘Crop Profitability’ was analyzed using ‘Benefit-Cost Ratio’ and ‘Impact of Groundwater Use on Gross Value Product’s was estimated using double log model. Results revealed that the net revenue generated from cropping was Rs. 32168 per month, whereas the monthly household expenditure of the farmers was Rs.33960, on average. Cropping alone cannot sustain the households’ livelihoods. With net income from livestock and non-farm income, farmers can meet their monthly household expenditure. Results of BCR show that all the crops are profitable, but this profitability is at the expense of over-fetching scarce groundwater. Wheat is the only crop with more than 1.19 kg/meter water productivity. Crops’ water productivity may decline if the water table keeps reducing. GVP of wheat and maize is negatively affected by the cost of groundwater. Cost sensitivity can be decreased if cost-efficient methods of irrigation are available. The government should regularize groundwater use through proper legislation and provide infrastructure/incentives for using other sources of water for irrigation as well. Availability of good quality seed to farmers should be ensured to enhance crop yield.

Electricity generation and China's GDP growth under dual control policy

To achieve the carbon neutralization plan by 2060, China implemented the “Dual Control” ( Neng Hao Shuang Kong in Chinese) policy in 2015 by limiting the energy intensity and consumption, leading to forced slowdown of energy-related production and consumptions, which in turn hampered China's economic growth. The economic impact of energy shortage has been discussed in such studies as Cheng et al., the economic consequences of the new policy remain unanswered. In this article, we select China's provincial GDP and electricity generation data from 2001 to 2021 to perform causality tests and a double log model which delineates the nexus between GDP growth and electricity generation. We find that (a) electricity generation growth Granger causes GDP growth but not vice versa, and (b) a 1% increase in electricity generation growth will lead to 0.17% increase in GDP growth. The significance of the finding is: as coal still primarily fuels electricity generation, dual control will further hinder China's economic development sans significant enhancement of electric system or expansion of renewable energy, our findings thus support an upgrade of current grid network by China Power International Development; an expansion of renewable capacity such as a proposal of 400 GW new energy project; and construction of energy storage devices such as the CGD Group thermal storage System and Yingcheng Compressed Air Energy Storage System.

Exploring the predictive power of ANN and traditional regression models in real estate pricing: evidence from Prishtina

PurposeThe purpose of the study is to examine the efficiency of linear, nonlinear and artificial neural networks (ANNs), in predicting property prices.Design/methodology/approachThe present study uses a dataset of 1,468 real estate transactions from 2020 to 2022, obtained from the Department of Property Taxes of Republic of Kosovo. Beginning with a fundamental linear regression model, the study tackles the question of overlooked nonlinearity, employing a similar strategy like Peterson and Flanagan (2009) and McCluskey et al. (2012), whereby ANN's predictions are incorporated as an additional regressor within the ordinary least squares (OLS) model.FindingsThe research findings underscore the superior fit of semi-log and double-log models over the OLS model, while the ANN model shows moderate performance, contrary to the conventional conviction of ANN's superior predictive power. This is notably divergent from the prevailing belief about ANN's superior predictive power, shedding light on the potential overestimation of ANN's efficacy.Practical implicationsThe study accentuates the importance of embracing diverse models in property price prediction, debunking the notion of the ubiquitous applicability of ANN models. The research outcomes carry substantial ramifications for both scholars and professionals engaged in property valuation.Originality/valueDistinctively, this research pioneers the comparative analysis of diverse models, including ANN, in the setting of a developing country's capital, hence providing a fresh perspective to their effectiveness in property price prediction.

An economic analysis of crop diversification and dynamics of cropping pattern in Karnataka, India

The extent and nature of crop diversification and dynamics of cropping pattern in Karnataka state has been analyzed using secondary data collected from different publish sources of Directorate of Economics and Statistics (DES), Bangalore, Karnataka from a period of 1998–99 to 2020–21 (i.e., 23 years). Composite Entropy Index (CEI), double log model and Markov chain analysis were applied to assess the determinants of crop diversification and dynamics of cropping pattern in Karnataka. Results of C.E.I indicates that Kodagu, Dakshina kannada, Yadgir, Udupi and Shivamogga has low crop diversification. Although Karnataka’s crop diversification values show a positive trend but its coefficient value is almost zero. It shows that there is a threat for Karnataka’s crop diversification. The transition probability matrix diagram indicated that although cereals and millet groups occupied a larger share in terms of area under crops, it has a negative net gain in the probability of area retention. Double log model results revealed that the variable like MSP of coarse cereal, percentage of gross irrigated area to net irrigated area, credit inflow in to agricultural sector by the scheduled commercial bank and length of national highways are influencing the crop diversification positively. Therefore, the establishment of fundamental infrastructure, such as reliable irrigation water supply, access to credit, and well-developed transportation networks, is a crucial prerequisite for creating favorable conditions to promote agricultural development and crop diversification. These parameters have been identified as influential factors that shape the nature and extent of crop diversification. By addressing these infrastructure needs, it becomes possible to foster an environment conducive to agricultural growth and facilitate the process of diversification.

Determinants of Agricultural Credit Acquisition Amongst Poultry and Fish Farmers in Selected LGA’s of Rivers State, Nigeria

The study analyzed the determinants of agricultural credit acquisition by poultry and fish farmers in Obio/Akpor and Port Harcourt Local Government Area, Nigeria. Simple random sampling technique was used to select 100 farmers from 10 communities in the study area. The objective of the studies are to, describe the socio-economic characteristics of the respondents, identify the sources of credits available to the farmers, determine factors influencing credit acquisition in the and analyse the constraints influencing farmers access to agricultural credit in the study area. The research instruments employed in the study were descriptive statistics, Likert scale and regression analysis. Research result for Obio/Akpor LGA, we used the double log model, said to be the best fit because it had the highest F ratio, 228.431, the highest number of significance variables, a significant Prob > F value of 0.000, an R- squared of 0.97- and an Adj R-squared of 0.965. Membership to cooperative and delay in credit disbursement was found to be significant factors. For respondents in Port Harcourt LGA. The semi- log model is said to be the best fit because it had the highest F ratio, the highest number of significance variables, a significant Prob > F value of 0.000, an R- squared of 0.964 and an Adj R-squared of 0.959. at 5%. Farmers are encouraged to join cooperatives to enable them acquire credits. Interest rate and delay in credit disbursement was found to be significant. The researcher recommends that credit and financial institutions review the conditions for credit acquisition by farmers, so that more persons will be able to benefit from credit disbursement especially with respect to high interest rate, collateral security and proximity to the farmers. Efforts should be made to creat e more awareness about the existence of formal agricultural credits.

Selecting correct functional form in consumption function: Analysis of energy demand at household level.

In the estimation of demand functions for energy resources, parametric econometric models of energy demand are commonly used to predict future energy needs. The functional forms commonly assumed in parametric energy demand models include linear functional forms, log-linear forms, trans-log models, and an almost ideal demand system. It is frequently debated which is the "best" functional form to employ in order to accurately represent the underlying relationships between the demand for various energy resources and explanatory variables such as energy prices, income, and other demographic factors. The study has focused on developing proper non-nested tests to compare the two demand systems, the double log model and the LA-AIDS model. C-test is used to test the validity of using the two parametric functional forms in models of residential energy demand. Cross-sectional household-level data of the Pakistan Social and Living Standards Measurement (PSLM) 2013-14 and Asian Development Bank (ADB) Asia and Pacific 2018 are used. Results indicate that the LA-AIDS model is better than the double log model. The estimated elasticity of own prices, cross-prices, and income in terms of spending, family size, and equipment are particularly important to producers and policymakers in making investment and incentive choices. A significant part of the budget for families is for electricity, natural gas, firewood, and other fuels; smaller budget shares are set down to other items such as kerosene oil, cylinder gas, and diesel. Household per capita demand for energy resources will rise over the next decade; therefore, the government needs to make progress on developing energy-saving strategies. If not addressed the issue properly, we may face energy shortages and high energy import bills.

The Effect of Village Income and Gross Regional Domestic Product on Poverty in Indonesia

The problem of poverty still exists today, and economic disparities are still found in districts/cities in Indonesia. The government has taken various ways to alleviate the problem of poverty, one of which is by distributing village funds to all corners of the country. Based on the data availability in Buku Saku Dana Desa and Buku Pintar Dana Desa published by the Ministry of Finance, Village income from 2015 to 2017 tends to increase. Meanwhile, the number of poor individuals throughout Indonesia between 2016 and 2017 has decreased. This paper attempts to examine whether or not Village Income, such as Village Funds, Revenue Sharing Taxes and Levies, Village Fund Allocations, and Village Original Income, as well as the GRDP (Gross Regional Domestic Product), affect the incidence of District/City poverty in Indonesia. This study uses secondary data from Statistics Indonesia for two years, consisting of 407 districts/cities in Indonesia each year. The regression analysis with static panel data using a double log model is the data analysis technique used in this article. The results show that Village Income and GRDP have an effect on poverty in districts/cities in Indonesia, with values of -0.0004 for Village Funds, 0.003 for Revenue Sharing Taxes and Levies, -0.026 for Village Fund Allocation, 0.002 for Village Original Income, and -0.197 for Gross Regional Domestic Product. We advise the government to increase village fund transfers, village fund allocation, and GRDP to lower poverty levels.

Determinants of Maize Yields among Small-Scale Farmers in Mbinga District, Tanzania

Maize plays a significant role in food security strategies in the world. It is the world’s most important food crop to majority of communities since it provides cheap source of essential calories as compared to other sources of protein foods. It has the potential of being grown in a variety of agro-ecological zones with varied yields per hectare. The main purpose of this study was to analyse the determinants of maize yields among small-scale farmers in Mbinga district, Ruvuma region, Tanzania. This cross-sectional study employed a multistage sampling method to select 120 farmers in the study area. Semi-structured questionnaires and key informant interviews were used for data collection. The data was analysed by descriptive statistics and multiple regression analysis (double-log model). The results indicate that farm size, amount of seed, fertilizer and labour were the significant determinants of maize yields among small-scale farmers in the district. The study recommends that; the government should ensure access to quality and affordable inputs to farmers by employing effective price control mechanisms on fertilisers and improved seeds which are imperative in improving the yields. Farmers should be capacitated on accessing affordable loans through financial inclusion programs and expand market access that can be reliable through the formation of farmers’ associations. Farmers should be exposed to better farming techniques such as the rational application of inputs through effective provision extension services.

Assessing the Impact of Aviation Noise on Housing Prices Using New Estimated Noise Value: The Case of Taiwan Taoyuan International Airport

Aviation noise at airports has a significant impact on nearby residents’ quality of life and residential property values. This study evaluated the impact of aviation noise based on house prices by using three different hedonic price models. Two novel independent noise variables, the estimated aviation noise value and noise reward fund are proposed for constructing effective hedonic price models. The real data of real estate transactions from the region defined by the Taoyuan International Airport’s 60–64 dB day-night average sound level (Ldn) and ≥65 dB Ldn noise contours are adopted as empirical data. Empirical results showed that the double-log hedonic price model with the proposed estimated aviation noise variables is the most suitable model for this study. Based on the double-log model, this study found that aviation noise has a significant negative impact on house prices in both noise contour areas of 60–64 dB Ldn and ≥65 dB Ldn. The rate of decline in house prices is approximately USD 2356.02/dB and USD 3622.78/dB in the 60–64 dB Ldn and ≥65 dB Ldn contour areas, respectively. Our results also showed that the noise reward fund had no significant impact on the house prices which implies that the current subsidy method has been maintained at an appropriate level for Taoyuan International Airport.

CONSIDERING CORRUPTION, INFLATION, INFRASTRUCTURE AND TRADE TO EXPLAIN FOREIGN DIRECT INVESTMENT INFLOWS IN INDIA POST LIBERALIZATION

This paper considers corruption, inflation, infrastructure and trade to fit models to explain the inflow of foreign direct investment in India post liberalization. For this purpose, data from 1995 to 2019 is used considering the consistent availability of data for all the variables during this period. Timeseries regression is performed on standardized independent variables to control for multicollinearity. Two models are estimatedone having a doublelog form and one without converting the explanatory variables into logarithms.It is found that corruption is signifi cant at 5% significance level in both the models. Trade is significant at 10% significance level in the doublelog model while it is insignificant in the other model. Also, infrastructural variables i.e. energy and transportation are both insignificant in doublelog model while energy is significant and transport is insignificant in the other model. Consumer price index is used in place of inflation as it does not make sense to convert inflation rate into logarithm. Itis found to be insignificant in both the models.

POLA KONSUMSI BERAS RUMAH TANGGA BERDASARKAN GOLONGAN PENDAPATAN DAN FAKTOR-FAKTOR YANG MEMPENGARUHINYA DI KOTA PALANGKA RAYA

Rice is a basic requirement for the people of Central Kalimantan Province. The biggest consumption of rice comes from household consumption. Households with different income levels will have different consumption patterns. With this situation, this research is important to determine how the pattern of household rice consumption is based on income groups and what factors influence the pattern of household rice consumption based on income groups in the City of Palangka Raya. This study uses primary data and secondary data. The research analysis uses descriptive analysis and quantitative analysis. Quantitative analysis uses multiple linear regression analysis with Ordinary Least Square (OLS). The econometric model used is the double log model assisted by using the Eviews 9.0 application. The results of the study showed that the factors that significantly influenced the consumption pattern of household income were the number of house members and the age of the household head. In the high income group the factors that significantly influence are the dummy marital status of the head of the household, the age of the head of the household has a positive effect and the number of household members has a negative influence and each has a significant effect on household rice consumption.

Financing Supply of Islamic Banking During COVID-19 Outbreak in Indonesia

This study aims to analyze the factors that affect the financing supply of Islamic banking during pandemic COVID-19 outbreak in Indonesia. The variable of financial performances of Islamic banking such as Return on Assets (ROA), Capital Adequacy Ratio (CAR), Financing to Deposit Ratio (FDR) and Non-Performing Financing (NPF) are used as the independent variables. Meanwhile, the impact of COVID-19 pandemic is analyzed using dummy variable. Furthermore, each of the independent variables and the dummy variable are tested its influence to the dependent variable, namely the financing supply of Islamic banking by using a proxy of the total financing. Ordinary Least Square (OLS) with double log model used as a data analysis technique with the results of the study show that the variable of ROA has a positive but not significant effect to the financing supply. Variable CAR and FDR each shows a negative and not significant effect to the financing supply. Whereas, the variable of NPF shows a negative and significant effect to the financing supply. Meanwhile, COVID-19 pandemic contributes in giving a positive and significant difference effect to the financing supply than before the presence of COVID-19 in Indonesia. The results of this study prove that the phenomenon of credit crunch in Islamic banking relative can be addressed during pandemic COVID-19 outbreak in Indonesia.

Modeling residential water demand: An approach based on household demand systems

Most estimations of residential water demand are based on single-equation models that rely on assumptions that are most often not compatible with the fundamental principles of consumer theory. In this paper, we relax these assumptions by using a more flexible system of demand estimation, the Quadratic Almost Ideal Demand System (QUAIDS) (Banks et al., 1997) and reveal the existence in our sample of substitution and complementary patterns as well as non-linearities in Engel curves for water consumption. Water demand would not be, therefore, linear in income and separable from other goods consumed within the household. In this context the QUAIDS functional specification is expected to be more consistent with observed consumer behavior. Our results seem to confirm this expectation; when compared to the linear, log-linear and double-log models commonly used in water demand estimation, QUAIDS seems to produce a better overall fit and a better fit to the asymmetric shape of the real distribution of water consumption. This has important implications in terms of public policy, as it allows to explore how water policies interact with other goods consumed within the household (e.g. water-energy nexus or efficient household appliances). Furthermore, differential responses to pricing policies and taxes across the income distribution can be considered, thus contributing to avoid undesired redistributive effects and water poverty.

Demand Analysis of Termite Control Service in Jakarta

Termite is an economically important pest species in the pest control industry and considered as one of the urban pests. Although it had caused a great loss, only a few studies on termite control demand were found. This study attempted to identify determinants and build the econometric model of termite control demand in Jakarta. The findings are expected to give the pest control industry a better understanding of the pest control market. Two ad-hoc models, linear and double log models, were investigated using the Least Square Dummy Variable (LSDV) technique. The results showed that the double log model was found better than the linear model based on sign expectation and significance. The price of termite control service, building permits, price of structural metals and dummy variables for the large company were statistically significant determinants, whereas dummy variables for risk class were not. Termite control demand for medium and small companies was not significantly different, but both of them were significantly lower than demand for the large company. This study also found that the demand for termite control was elastic.Keywords: demand analysis, econometric modeling, pest control, termite control, urban pest

Buoyancy Estimates of Malaysia's Tax System 1961 – 1998

Several criteria are used to determine a 'good tax system' and they include administrative feasibility, ensuring burden of tax is spread fairly among taxpayers and tax buoyancy. Tax buoyancy measures the responsiveness of tax revenue to income growth. Previous studies have assumed a constant buoyancy estimate for the period under study and hence applied a double-log tax model (Mansfield, 1972; Choudhry, 1975; Byrne, 1983). In practice, however, tax buoyancies may change over time due to inflation, changing tax bases, improved tax administration and stricter enforcement of tax law by revenue authorities. This study uses the Box-Cox tax model which allows the determination of inter-temporal tax buoyancies for the period 1961-1998. The results obtained revealed a steady decline in buoyancy estimates of less than one for both direct and indirect taxes implying inefficiencies in the tax system. Suggestions are made to revamp the current tax system by integrating existing indirect taxes such as sales and service tax into a single broad-based consumption tax.

Effects of area characteristics and municipal waste collection fees on household waste generation

This study attempted to calculate the amount of waste generated by the residents, households and commercial businesses in Songkhla and Hat Yai cities under three potential scenarios: (1) status quo—no charge for waste collection service (current situation); (2) an equal fee charging rate for constituents of both Songkhla and Hat Yai cities as stated in the Public Health Law of Thailand; (3) a different waste collection fee within the cities of Songkhla and Hat Yai as proposed and concluded in the study of Siritorn (Presented at the APBERS conferences in Japan, 2017, Ritsumeikan Asia Pacific University, Beppu, 2017). The regression results of the double-log model indicated that different optimal rates for waste collection fee in each city would decrease the waste produced in Songkhla by 162 kg per day and decrease waste production by 503 kg per day in Hat Yai. As a result, the two municipalities could generate a double benefit of (1) savings from total expenditure on waste management and (2) savings from the adjustment of behaviour of the residents to create a decrease in the present waste production total amounts. In summary, the “different” fee policy strategy created a win–win situation for the municipalities.

Investigation of price fluctuation in retail fish species marketing in Ibadan, Oyo State

This study investigated price fluctuation in retail fish marketing in Ibadan metropolis for two years. A total of 120 respondents were interviewed in the study and primary data was used through questionnaires with interview. Data obtained were analyzed using descriptive statistics and regression model. The questionnaires were distributed randomly in ten selected markets chosen cut across five local governments in Ibadan metropolis. The descriptive statistics showed that 95.0 percent of the fish sellers were women and 5.0 percent were male. The respondents were married, 9.2 percent had no formal education, 30 percent had primary education, and 14.2 percent had secondary education while 4 percent had tertiary education. Also, about 65.8 percent of the respondents were with 1 to 10 years experience in fish marketing while 3 to 4% had 21 to 30 years of fish marketing experience. Double-log model was found to be the lead equation among the four models fitted. The model indicated a relationship between the determinants of fish price fluctuation in retail fish marketed (Y) and some explanatory variables which include trading experience (X1), Education level (X2), Average stocks (X3), hoarding quantity (X4), government daily tax rate (X5), and fuel price (X6). All these were found to be significant at 1 percent level. The elasticity of all variables determining fish price fluctuation was less than one. This means that they were inelastic. Thus, a unit increases in the trading experience lead to N0.1974 decrease in fluctuation of price of fish between the two years. Also, a unit increase in the quality of stock hoarded lead on the average of N0.3078 unit increase in the fluctuation in price within two years. Some of the major problems faced by fish retailers in the study area include: problem of middlemen, storage facilities, erratic power supply and government rate/tax.

Trend of global carbon emissions with special reference to economy, energy, finance, forest, urbanisation and trade openness: An analysis

Global warming coupled with a staggering level of greenhouse gas (GHG) emissions has pushed our planet to a brink of irreversibility. Concentration of atmospheric carbon dioxide (CO2), one of the major GHGs, today is more than ever seen in 3 million years of human history. An elaborate play of multiple factors has led us to this situation so extreme and hazardous. This paper examines the relationship between CO2 emissions and relevant factors using a multivariate linear and double-log regression model taking economic growth, energy consumption,forestcover, financial development, urbanisation and trade openness as variables across 55 countries with different levels of development. The findings indicate significant causal relationships between the factors, underlining crucial aspects that can majorly benefit climate change research and policymaking. Results emphasize the need to reverse the trend of increasing emissions while moving on to a phase of greener growth and healthier economic practices, based on unconventional energy sources and appropriate policy making.

Visualization and statistical modeling of financial big data: double-log modeling with skew-symmetric error distributions

This study considers the visualization and statistical modeling of financial data (e.g., sales, assets, etc.) for a large data set of global firms that are listed and delisted. We present exploratory data analysis carried out in the R programming language. The results show that a double-log model with a skew-t error distribution is useful for modeling a firm’s total sales volume (in thousands of U.S. dollars) as a function of its number of employees and total assets (in thousands of U.S. dollars). This result is obtained by comparing the Akaike information criteria of several double-log models with independent and identically distributed random error terms with skew-symmetric distributions and by further evaluating the models using cross-validation.