Unrelated Regression Approach Research Articles

ANALISIS PEMBANGUNAN SEKTOR KEUANGAN PADA SEKTOR JASA DI INDONESIA

Analyze how Financial Sector Development can affect the Service Sector in Indonesia using the Seemingly Unrelated Regression approach during the 2008-2015 period. This study uses quarterly data in the period 2008.1 - 2015.4. The year 2008 was taken as the beginning of observing the equation model because the period after the global crisis affected the global financial sector. The analysis tool used in this study uses a regression model with the SUR (Seemengly Unrelated Regression) approach. Using the existing model approach, it was concluded that the determinants of the gross national savings model in the service sector in Indonesia were influenced by the stock market index, gross domestic product, and real sector bank loans. The determinants of the banking credit model in the service sector in Indonesia are influenced by variables of the financial sector development index, stock market index, gross domestic product, service sector output, and gross national savings. While in the investment model equation, there are no variables that affect investment in the service sector. This is because there is a time lag in determining investment. Finally, the determinants of the output model in the service sector in Indonesia as well as the banking sector credit equation are influenced by the variables of the banking sector development index, stock market index, gross domestic product, service sector output, and gross national savings.

The nexus between financial development, globalization, and environmental degradation: Fresh evidence from Central and Eastern European Countries.

Global warming and greenhouse gas emissions have become a severe threat to our ecosystem. Prior studies on environment posit that ample exhaustion of fossil fuels for energy is one of the fundamental causes of environmental degradation and naturally replenished energy sources are affordable over fossil fuels. This study set out to examine the role of financial sectors and globalization (in the presence of energy and renewable energy consumption) for a sustainable environment in the panel of Central and Eastern European (CEE) countries in One Belt and One Road initiative perspective. The current study uses annual data of 16 CEE countries covering the period of 1980 to 2016. After confirmation of cross-sectional dependency and co-integration among variables, we applied the Dynamic Seemingly Unrelated Regression and Dumitrescu-Hurlin causality approach for long-run estimations and to check the causal relationship, respectively. The empirical findings of the study certify the existence of an environmental Kuznets curve for the selected panel countries. Globalization is enhancing the environmental quality of the CEE economies. It is important to note that energy consumption and renewable energy consumption have a positive and statistically significant whack on carbon emission. In addition, we do not find a significant link between financial development and carbon emission. Granger casualty test confirms a two-way causal relationship between economic growth and carbon emission, globalization and environmental degradation, globalization and renewable energy consumption, economic growth and renewable energy consumption, and between financial development and energy consumption. Moreover, we found one-way causality from energy consumption (renewable and non-renewable) to carbon emissions. Based on the findings, a number of appropriate policy suggestions are presented in the perspective of Central and Eastern European Countries.

Aggregate road passenger travel demand in New Zealand: A seemingly unrelated regression approach

Road passenger transportation, which includes private vehicles, public transport, and motorcycles, is regarded a vital link that connects people and economic activities across New Zealand. Given the fact that road passenger transport modes are considered substitutes/complements to one another, there is a strong possibility that an interrelationship exists between the travel demand functions, primarily due to the correlation between their disturbances. This research gap is addressed in this study using a seemingly unrelated regression (SUR) method. The objective of this paper is twofold. First, the study examines whether the error terms of the demands for the four main road passenger transport choices: petrol cars, diesel cars, buses and motorcycles, respectively, are correlated. Second, the study identifies factors that have significant impact on the demand for each available road passenger transport choice. Empirical result from the Breusch-Pagan test of independence confirms the existence of correlated error terms in the demand equations. Moreover, estimated results from the SUR model also highlight various policy implications, including: implementing a fuel tax in the short-run to reduce the travel demand by both petrol and diesel car users, subsidising public transport providers, and several opportunities to alleviate the first-/last-mile problem associated with public transit. Recommendations for further research include developing regional analysis to compare the dynamics of different cities and constructing a forecasting model for private and public transport, and motorcycles, given detailed assumptions about energy and economic conditions.

Impact of financial development and economic growth on environmental quality: an empirical analysis from Belt and Road Initiative (BRI) countries.

This study aims to analyze the impact of financial development, foreign direct investment, economic growth, electricity consumption, and trade openness on environmental quality for a panel of 59 Belt and Road Initiative (BRI) countries, over the period of 1980-2016. The presence of the environmental Kuznets curve (EKC) hypothesis is investigated. The cross-sectional augmented Dickey-Fuller (CADF) and cross-sectional Im, Pesaran, and Shin panel unit root test; the Westerlund cointegration test, the dynamic seemingly unrelated regression (DSUR) approach; and the Dumitrescu and Hurlin (Econ Model 29:1450-1460, 2012) panel causality approach are employed. It is found that the analyzed variables are stationary at first differences and are cointegrated. It is also found that an increase in financial development, foreign direct investment, and trade openness enhance environmental quality, while the increase in economic growth and electricity consumption degrade environmental quality. The presence of the EKC hypothesis for the selected panel countries is validated. Furthermore, the Dumitrescu-Hurlin (DH) panel causality test result confirmed the presence of bidirectional causality among economic growth, foreign direct investment, financial development, electricity consumption, and trade openness with environmental quality.

Fuel economy gaps within and across garages: A bivariate random parameters seemingly unrelated regression approach

The key objective of this study is to investigate the interrelationship between fuel economy gaps and to quantify the differential effects of several factors on fuel economy gaps of vehicles operated by the same garage. By using a unique fuel economy database (fueleconomy.gov), users’ self-reported fuel economy estimates and government’s fuel economy ratings are analyzed for more than 7000 garages across the United States. The empirical analysis, nonetheless, is complicated owing to the presence of important methodological concerns including potential interrelationship between vehicles within the same garage and unobserved heterogeneity. To address these concerns, bivariate seemingly unrelated fixed and random parameter models are presented. With government’s test cycle ratings tending to over-estimate the actual on-road fuel economy, a significant variation is observed in the fuel economy gaps for the two vehicles across garages. A wide variety of factors such as driving style, fuel economy calculation method, and several vehicle-specific characteristics are considered. Drivers who drive for maximum gas mileage or drives with the traffic flow have greater on-road fuel economy relative to the government’s ratings. Contrarily, volatile drivers have smaller on-road fuel economy relative to the official ratings. Compared to the previous findings, our analysis suggests that the relationship between fuel type and fuel economy gaps is complex and not unidirectional. Regarding several vehicle and manufacturer related variables, the effects do not just significantly vary in magnitude but also in the direction, underscoring the importance of accounting for within-garage correlation and unobserved heterogeneity for making reliable inferences.

Multi-level urban form and commuting mode share in rail station areas across the United States; a seemingly unrelated regression approach

Transit-friendly development has recently become a popular strategy to increase transit mode share in the United States. Many policies and programs have been proposed and implemented across the country to increase residential and job densities, walkability, and mixed-use development around major transit stations in order to encourage transit ridership. Using data from all rail transit stations across the United States, this paper presents an analysis of commute mode share for people who live within walking distance to rail transit with regard to the urban form at both neighborhood and regional levels. This study provides additional evidence to better understand how transit accessibility and urban design jointly aim to encourage transit use and reduce driving in rail stations areas across the U.S. and thus cope with ever-growing traffic congestion in urban areas. It is one of the first analyses to examine the relationships between urban form measured at both local/neighborhood and metropolitan levels and the commuting mode share across major transit station areas nationwide. It utilizes a Seemingly Unrelated Regression modeling method (SUR) -which is based on generalized least squares (GLS)- and estimates three primary modes of auto, transit, and walk/bike.Findings suggest that urban form at both station area (local effect) and at the whole metropolitan area (regional effect) influences commuting patterns. Factors such as population and employment densities, walkability, and transit accessibility at both local and regional levels are significantly associated with commute mode share. Job accessibility via transit in the entire region (measured by the number of jobs located within 45 min from a transit stop) is another important factor encouraging transit ridership for every-day commuting trips.

Additive tree biomass equations for Betula platyphylla Suk. plantations in Northeast China

A new system of additive tree biomass equations was developed for juvenile white birch plantations based on tree diameter at breast height (DBH) and tree height (HT). Compared with previous equations developed for natural white birch forests, the new system included one more biomass component and provided more accurate predictions. Accurate estimates of tree component and total biomass are necessary for evaluating alternative forest management strategies for biomass feedstock, carbon sequestration, and products. Previous biomass equations developed for white birch trees in natural stands provided substantially biased predictions for white birch plantations. A new system of additive tree biomass equations was developed for juvenile white birch plantations in the northeastern China. With destructive biomass sampling data from 501 trees sampled from white birch provenance and family trails at ages 7, 9, 10, and 13 in three provinces, a system of nonlinear additive tree biomass equations based on DBH and tree height was developed using the nonlinear seemingly unrelated regressions (NSUR) approach. Compared with previously published equations developed for natural white birch forests, the new system provided more accurate predictions of white birch tree component and aboveground and total biomass, especially of branch, foliage, and root biomass. The new system extended the applicability of biomass equations to white birch plantations in the northeastern China.

Discrete-Choice Modeling Of Non-Working Women’s Trip-Chaining Activity Based

Start The urban developments of technology and economics are now changing the lifestyles of the urban societies. It is also changing their travel demand to meet their movement needs. Nowadays, urban women, especially in Bandung, West Java, have a high demand for their daily travel and tend to increase. They have the ease of accessibility to personal modes of transportation and freedom to go anywhere to meet their personal and family needs. This also happens to non-working women or as housewives in the city of Bandung. More than 50% of women’s mobility is outside the home, in the term of trip-chaining, from leaving to returning home in one day. It is based on their complex activities in order to meet the needs of family and home care. While less than 60% of male’s mobility is outdoors, it is a simple trip-chaining or only has a single trip. The trip-chaining has significant differences between non-working women and working-men. This illustrates the pattern of Mom and Dad’s mobility in a family with an activity-based approach for the same purpose, i.e. family welfare. This study explains how complex the trip-chaining of non-working urban women and as housewives, with an activity-based approach done outdoors in a week. Socio-economic and household demographic variables serve as the basis for measuring the independent variables affecting family welfare, as well as the variables of type, time and duration of activities performed by unemployed housewives. This study aims to examine the interrelationships between activity variables, especially the time of activity and travel, and socio-economic of household variables that can generate the complexity of women’s daily travel. Discrete Choice Modeling developed by Ben-Akiva, Chandra Bhat, etc., is used in this study to illustrate the relationship between activity and socio-economic demographic variables based on primary survey data in Bandung, West Java for 466 unemployed housewives. The results of the regression, by Seemingly Unrelated Regression approach methods, showed the interrelationship between all variables, including the complexity of trip chaining of housewives based on their daily activities. The type of mandatory and discretionary activities, and the duration of activities performed during the dismissal in the series of trip chains conducted are intended for the fulfillment of the welfare of all family member.

The Effects of Changing Climate and Market Conditions on Crop Yield and Acreage Allocation in Nepal

This study examines the impact of changing climate and product market conditions on crop yield and land allocations in Nepal. Zellner’s seemingly unrelated regression approach is used to estimate the acreage and yield functions. The potential impact of price endogeneity on estimated parameters is corrected using an instrumental variable method. The results show that farm input prices and output prices play a crucial role in determining acreage allocation. While the variation in daily temperature during planting season affects acreage allocations for all crops except wheat, the total precipitation is critical for upland crops, particularly for millet. Literacy rate and the number of rainy days significantly affect yield for most crops. Moreover, the rising winter warming is enhancing wheat and potato yields. The results also show that a ten percent decrease in the number of rainy days during the growing season is likely to reduce yields for rice, maize, and wheat by 4.8, 1.7, and 0.8 percent, respectively.

Province specific impacts of the 2006 United States-Canada Softwood Lumber Agreement: A seemingly unrelated regression approach

In this paper, we evaluate effects of the 2006 U.S.-Canada Softwood Lumber Agreement (SLA 2006) in U.S. lumber imports from Canadian provinces. Based on monthly data from January 1988 to October 2015, we estimate a system of U.S. softwood lumber import equations by using Seemingly Unrelated Regression approach. The results reveal that SLA 2006 had a negative impact on softwood lumber shipments to the U.S. from British Columbia, Ontario, Quebec, and Saskatchewan, and no effect on those from SLA-exempted provinces. Thus, SLA 2006 did not provide an opportunity for trade diversion from SLA covered provinces to exempted provinces.

Determinants of nitrogen surplus at farm level in Swiss agriculture

This paper investigated the determinants of nitrogen surplus, also denoted as nitrogen balance, at farm level in Swiss agriculture. Our analysis was based on a cross-section of 210 farms from the year 2010. The nitrogen surplus of each farm was estimated according to the OECD soil-surface approach and decomposed in two components—nitrogen intensity and nitrogen inefficiency. The average nitrogen surplus of the farms investigated amounted to 89 kg/ha, resulting from an average nitrogen intensity of 255 kg/ha and an average nitrogen inefficiency of 34%. The determinants of nitrogen surplus and its two components were analyzed by means of a three-equation regression model estimated using a robust seemingly unrelated regression approach. Farm size, part-time farming, organic farming, arable cropping and farmer’s age were found to decrease nitrogen surplus, whereas dairy, pig and poultry farming were associated with an increase in nitrogen surplus.

Determinants of International Tourism Flows to the Republic of Croatia: An SUR Analysis of Panel Data from 1993-2015

Abstract: This paper examines origin-effects of tourist flows into Croatia from 1993-2015, a time period that features several important events: the fragmentation of Yugoslavia, the European recession, and Croatia’s accession to the European Union. Applying the seemingly unrelated regression (SUR) approach to a large panel data set with the number of annual arrivals from each origin country as the dependent variable, we identify and analyze the determinants of tourism flows to Croatia. A series of augmented gravity model specifications reveals that inflows can be explained by geographic proximity, GDP per capita, origin country population, and openness. The role of the real exchange rate variable is inconclusive, and in fact problematic for years 1993-95 when hyperinflation plagued the region in the wake of Yugoslavia’s dissolution. The results confirm the validity of the models, both for the subset of origin countries and for the subset of non-origin countries for which otherwise complete data are available. Given the importance of tourism to Croatia’s national accounts position, implications for tourism policy are discussed, as are suggestions for future research. Keywords: Tourism Origin-Effects, Gravity Model, Croatia JEL Classification: C33, O52, Z3

Drivers of the Variation in Prosthetic Implant Purchase Prices for Total Knee and Total Hip Arthroplasties

BackgroundPrevious studies have documented wide variation in health care spending and prices; however, the causes for the variation in supply purchase prices across providers are not well understood. The purpose of this study was to determine the drivers of variation in prosthetic implant purchase prices for primary total knee and hip arthroplasties (TKA and THA, respectively) across providers. MethodsWe obtained retrospective data from 27 hospitals on the average prosthetic implant purchase prices for primary TKAs and THAs over the 12 months ending September 30, 2013, as well as data on a range of independent potential explanatory variables. Each hospital performed at least 200 primary total joint arthroplasties per year. The multivariate seemingly unrelated regression approach was used to evaluate the impact of the variables on purchase price for each type of implant. ResultsThe average purchase price at the hospital at the 90th percentile was 2.1 times higher for TKAs and 1.7 times higher for THAs than that at the hospital at the 10th percentile. The use of a hospital–physician committee for implant vendor selection and negotiation was associated with 17% and 23% lower implant purchase prices (P < .05) for TKAs and THAs, respectively, relative to hospitals that did not have this collaborative approach. ConclusionThe use of a joint hospital–physician committee is a potential strategy for achieving lower average purchase prices for prosthetic implants. Policies to increase hospital–physician collaboration may lead to lower average purchase prices in this market.

Seemingly Unrelated Regression Approach for GSTARIMA Model to Forecast Rain Fall Data in Malang Southern Region Districts

Time series forecasting models can be used to predict phenomena that occur in nature. Generalized Space Time Autoregressive (GSTAR) is one of time series model used to forecast the data consisting the elements of time and space. This model is limited to the stationary and non-seasonal data. Generalized Space Time Autoregressive Integrated Moving Average (GSTARIMA) is GSTAR development model that accommodates the non-stationary and seasonal data. Ordinary Least Squares (OLS) is method used to estimate parameter of GSTARIMA model. Estimation parameter of GSTARIMA model using OLS will not produce efficiently estimator if there is an error correlation between spaces. Ordinary Least Square (OLS) assumes the variance-covariance matrix has a constant error 𝜀𝑖𝑗~𝑁𝐼𝐷(𝟎,𝝈𝟐) but in fact, the observatory spaces are correlated so that variance-covariance matrix of the error is not constant. Therefore, Seemingly Unrelated Regression (SUR) approach is used to accommodate the weakness of the OLS. SUR assumption is 𝜀𝑖𝑗~𝑁𝐼𝐷(𝟎,𝚺) for estimating parameters GSTARIMA model. The method to estimate parameter of SUR is Generalized Least Square (GLS). Applications GSTARIMA-SUR models for rainfall data in the region Malang obtained GSTARIMA models ((1)(1,12,36),(0),(1))-SUR with determination coefficient generated with the average of 57.726%.

Changes in intra-city employment patterns: a spatial analysis

Purpose – The purpose of this paper is to investigate area-level labour market dynamics from a spatial perspective. This analysis is aimed at better understanding what socio-economic actors are associated with shifts in unemployment rates across a major metropolitan city. Design/methodology/approach – Based on two waves of New Zealand census data, this paper combines a seemingly unrelated regression approach (allowing for relaxation of the assumption that residuals from models of different employment states are unrelated) with a spatial lag model. Findings – The key socio-economic drivers associated with intra-city employment dynamics were vehicle access, dependency rates and educational attainment. Importantly, the identification of spatial autocorrelation with respect to employment status patterns within this major New Zealand city motivates a case for heterogeneous employment policies across the city. Originality/value – This research improves the understanding of changes in labour market status rates within a city region. This is done by inclusion of two important considerations: a spatial perspective to labour market dynamics at an intra-city level; and formally modelling the interdependence across the four potential labour market outcomes (being full-time, part-time, unemployed or out of the labour force). Overall, there was clear empirical support for the need to include spatial considerations when using targeted policy to help lift areas out of unemployment.

National Culture, Economy, and Customer Lifetime Value: Assessing the Relative Impact of the Drivers of Customer Lifetime Value for a Global Retailer

Customer lifetime value (CLV), a metric used in many industries, is based on the cumulated cash flow a customer accrues during his or her lifetime. Firms have used CLV as a basis for formulating and implementing customer-specific strategies; however, these can vary across countries because of each country's cultural and economic influences. Typically, CLV is computed with three components: purchase frequency, contribution margin, and marketing costs. In this study, the authors demonstrate that national cultural dimensions affect the drivers of purchase frequency and contribution margin and that economic factors influence the components of CLV directly. They use customer-level transaction data from a global retailer for a random sample of customers in 30 representative countries over a six-year period. They estimate the model using a seemingly unrelated regression approach while accounting for the heterogeneity of customers across countries and the endogeneity of marketing costs incurred by the firm. The results indicate that global retailers should pay attention to the dimensions of national culture and economic conditions because of their differential impact on CLV.

Proximity to Natural Amenities: A Seemingly Unrelated Hedonic Regression Model with Spatial Durbin and Spatial Error Processes

AbstractThe existing literature suggests that the presence of natural amenities, such as open spaces, can be highly valued and affect economic decisions about where people live and work. This article contributes to previous research by testing this hypothesis using a unique micro‐level data set and by examining spatial variations in income levels and housing prices in the presence of natural amenities in a case study of Arizona. Proximity effects are estimated based on a geographic information system road network in which each variable represents the road mile distance from house i to its closest natural amenity within each category. Using a seemingly unrelated regression approach, spatial hedonic regressions of housing prices and income levels indicate that the total effect of various natural amenities calculated for the sample average income household and average home value, ranges from $2,382 (National Forests) to $1,560 (Wilderness areas). The presence of compensating differentials has policy relevance in considering the regional value of natural amenities. It also implies that valuation approaches such as the travel cost method may not reflect the full price of recreation site access, and may lead to underestimates of such values.

Empirical equations for estimating aboveground biomass of &lt;i&gt;Betula pendula&lt;/i&gt; growing on former farmland in central Poland

We determined empirical models for estimating total aboveground as well as stem, branches, and foliage dry biomass of young (age up to 16 years) silver birch (Roth.) growing on the post-agricultural lands. Two sets of allometric models for trees with a height below or above 1.3 m (small and large trees respectively) were developed. Simplified models were elaborated based exclusively on appropriate tree diameter (diameter at ground level for small trees, diameter at breast height for large trees), while expanded models also included tree height. Total aboveground biomass was estimated as the sum of biomass of all tree components. To assure additivity of the developed equations, the seemingly unrelated regression approach for the final model fitting was used. Expanded models in both tree groups were characterized by a better fit to the data (Rfor total aboveground biomass for small and large trees equaled 0.8768 and 0.9752, respectively). Diameter at breast height appeared to be a better predictor than diameter at ground level – simplified models had better fit for large trees (R for total aboveground biomass equals 0.9611) than for small ones (R = 0.7516). The developed equations provide biomass predictions consistent with available Latvian, Estonian, Finnish, Swedish, and Norwegian models for silver birch.Betula pendula 2 22

Corporate Social Responsibility and Firm Debt Maturity

In this article we extend the streams of research on the capital structure of socially responsible firms by studying the impact of Corporate Social Responsibility (CSR) on firm debt maturity. Using a large sample of US firms, we find robust evidence that high CSR firms significantly reduce their debt maturity. In particular, our findings suggest that diversity and community are the dimensions which matter the most in explaining firm debt maturity. Furthermore, our results also show that firm characteristics influence the relationship between CSR and firm debt maturity. Finally, additional tests suggest that high CSR firms substitute shareholders’ equity for long-term debt. This result also holds when using a seemingly unrelated regression approach: CSR decreases the extent to which investments are financed with long-term debt and increases the extent to which investments are financed by short-term debt and shareholders’ equity. Overall, our results support the demand-side view that socially responsible firms use debt maturity to manage CSR overinvestment problems, as well as to signal their high quality and their access to the debt market.

Additive Tree Biomass Equations for Midrotation Loblolly Pine Plantations

Biomass estimation is a prerequisite for calculating biomass energy, carbon storage, and sequestration of forests and for examining forest productivity and nutrient cycling. With destructive biomass sampling data from 456 sampled trees on 114 plots of loblolly pine culture and density studies at ages 12, 15, and 16, two systems of nonlinear additive tree biomass equations were developed. One was based on DBH, tree height, live crown length and width, and diameter at live crown base, and the other was based on DBH and tree height only. The systems guarantee additivity in biomass equations. The nonlinear seemingly unrelated regressions (NSUR) approach was used to account for the inherent correlation among the biomass equations, and heteroscedasticity was addressed by having a unique weighting function for each equation. 1 Both systems of biomass equations were compared with previously published equations and the new ones provided more accurate predictions, especially with respect to branch and foliage biomass. The new systems can be used to accurately estimate tree component or total tree aboveground biomass of midrotation loblolly pine plantations in the southeastern United States.