Unrelated Regression Approach Research Articles

The long and variable lags of monetary policy: Evidence from disaggregated price indices

We study how monetary policy affects subcomponents of the Personal Consumption Expenditures Price Index (PCEPI) using local projections. Following a monetary policy contraction, the response of aggregate PCEPI turns significantly negative after over three years. There are stark differences in the timing and magnitude of the responses across price categories, including some prices that show an initially positive response. We discuss theoretical interpretations of our findings and point to useful directions for future theoretical research. We also show how to re-aggregate our cross-sectional estimates and their standard errors, taking into account dependence between different prices using a Seemingly Unrelated Regression approach. Re-aggregation exercises show that changes in expenditure behavior have not accelerated the long-lagged response of inflation to monetary policy.

Exploring Heterogeneity in Cost-Effectiveness Using Machine Learning Methods: A Case Study Using the FIRST-ABC Trial.

The aim of this study was to explore heterogeneity in the cost-effectiveness of high-flow nasal cannula (HFNC) therapy compared with continuous positive airway pressure (CPAP) in children following extubation. Using data from the FIRST-line support for Assistance in Breathing in Children (FIRST-ABC) trial, we explore heterogeneity at the individual and subgroup levels using a causal forest approach, alongside a seemingly unrelated regression (SUR) approach for comparison. FIRST-ABC is a noninferiority randomized controlled trial (ISRCTN60048867) including children in UK paediatric intensive care units, which compared HFNC with CPAP as the first-line mode of noninvasive respiratory support. In the step-down FIRST-ABC, 600 children clinically assessed to require noninvasive respiratory support were randomly assigned to HFNC and CPAP groups with 1:1 treatment allocation ratio. In this analysis, 118 patients were excluded because they did not consent to accessing their medical records, did not consent to follow-up questionnaire or did not receive respiratory support. The primary outcome of this study is the incremental net monetary benefit (INB) of HFNC compared with CPAP using a willingness-to-pay threshold of £20,000 per QALY gain. INB is calculated based on total costs and quality adjusted life years (QALYs) at 6 months. The findings suggest modest heterogeneity in cost-effectiveness of HFNC compared with CPAP at the subgroup level, while greater heterogeneity is detected at the individual level. The estimated overall INB of HFNC is smaller than the INB for patients with better baseline status suggesting that HFNC can be more cost-effective among less severely ill patients.

A simple approach to dealing with partial contestation

AbstractObjectiveWe propose a simple approach to dealing with partial contestation in models of multiparty elections.MethodsOur proposed approach is to add a tiny value to the vote share of parties that do not contest a district and then to include dummy variables identifying those districts in which parties do not compete. We can then estimate a single system of equations using a seemingly unrelated regression (SUR) approach and Aitchison's log‐ratio transformation. In our SUR system, we interact the dummy variable for a party that partially contested districts with other predictors in the equation that uses the share of votes of the same party in the log‐ratio outcome. Finally, we estimate robust standard errors for predictors in this equation to address heteroscedasticity.ResultsWe demonstrate the utility of our approach using simulated data and election results from the English parliamentary elections in 2017.ConclusionFrom our simulations, we find that our recommended approach performs as well as that proposed by Tom, Tucker, and Wittenberg. Our strategy is advantageous in that it is easy to estimate, uses information from all districts, and addresses partial contestation in real‐world elections with a single system of seemingly unrelated regressions.

Biomass Estimation and Carbon Storage of Taxodium Hybrid Zhongshanshan Plantations in the Yangtze River Basin

As a pivotal wetland tree, Taxodium hybrid Zhongshanshan has been widely planted in the region of Yangtze River for multipurpose of ecological restoration, field shelter, landscape aesthetics as well as carbon sequestration. However, the carbon allocation patterns across distinct stages of stand development of T. Zhongshanshan are poorly documented. Using a sample of 30 trees which were destructively harvested, this study compared 3 models for assessing aboveground biomass. Furthermore, a linear seemingly unrelated regression (SUR) approach was introduced to fit the system of the best selected model that ensured the additivity property. On this basis, biomass and carbon storage of T. Zhongshanshan stands in the Yangtze River Basin (YRB) were fairly estimated. Specifically, the study developed height-diameter at breast (H-DBH) function. The results showed that the selected 3-parameter polynomial model performed better, and the SUR approach provided more accurate estimates of leaf and stem fractions. The total tree biomass was 53.43, 84.87, 140.67, 192.71 and 156.65 t ha−1 in the 9-, 11-, 13-, 15-, and 22-year-old T. Zhongshanshan stands, and contributed averagely 94.40% of the ecosystem biomass accumulation. The current T. Zhongshanshan stands in the YRB area can store 124.76 to 217.64 t ha−1 carbon, of which total tree ranges from 25.32 to 90.89 t ha−1, with 55.19% to 77.66% storing in the soil. The T. Zhongshanshan had continuous potential for carbon storage during its growth, particularly in the incipient stages. The findings of this research are firsthand information for forest managers for the sustainable management of T. Zhongshanshan in the YRB and similar subtropical areas.

Do Oil Price Shocks Matter for Environmental Degradation? Evidence of the Environmental Kuznets Curve in GCC Countries

This paper aims to examine the asymmetric impact of oil price shocks on environmental degradation for a panel of six Gulf Cooperation Council (GCC) countries from 1996 to 2016. We use the dynamic seemingly unrelated regressions (DSUR) approach that considers cross-sectional dependency to reveal the interrelations between oil price shocks and carbon dioxide (CO2) emissions. The finding shows that the positive shocks of oil prices have a statistically significant negative effect on CO2 emissions, while negative shocks of oil prices did not affect CO2 emissions. More specifically, the positive oil price shocks have negatively influenced the CO2 emissions in Oman, Bahrain, Saudi Arabia, Qatar, and United Emirates Arab. In turn, the most negative effect is found in Qatar and Saudi Arabia. Meanwhile, the negative shocks of oil prices have statistically significant effects on the CO2 emission of Oman and Saudi Arabia. While for other countries, it does not have a significant impact. Also, the results support an environmental Kuznets curve in Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates; in contrast, the hypothesis was rejected in Bahrain and Oman. This study could help policymakers adopt renewable energy policies and use energy-saving technologies to sustain economic development and improve environmental quality.

The impact of supply chain relationship configurations on supplier performance: investigating buyer–supplier relations in the aerospace industry

Purpose A supplier may sell not only to one buyer (sole relationship configuration) but also to the buyers competitors (shared relationship configuration) for a specific product category. This study examines the performance implications when suppliers establish shared relationships with the buyer’s competitors.Design/methodology/approach Secondary data are used to test hypotheses relating a supplier’s relationship configurations to its operational performance. A seemingly unrelated regression approach (SUR) is applied to analyze the data, followed by endogeneity checks of the empirical findings.Findings The study shows that suppliers with less-shared ties with buying firms’ competitors exhibit superior inventory efficiency and asset turnover. Thus, suppliers can improve operational efficiency by creating relatively exclusive, deep and trust-based relations instead of more extensively shared and shallower relationships.Research limitations/implications Based on agency theory as a theoretical lens and aerospace industry data, this research contributes by addressing the supplier’s perspective and linking its operational efficiency performance with its chosen supply relationship configuration.Practical implications Suppliers need to understand the performance implications of choosing relatively exclusive relationships versus shared relationships with buying firms. The research provides new insights for managers and can guide their supply chain decision-making.Originality/value Little is known about how a supplier’s relationship configurations can elevate, or impair, its operational efficiency. While conventional wisdom holds that suppliers should focus on multiple avenues of revenue growth by selling to buyers’ competitors, this study demonstrates that more sales to a buying firm’s rivals might, in fact, reduce a supplier’s efficiency.

Implications of public corruption for local firms: Evidence from corporate debt maturity

Using political corruption conviction data from the U.S. Department of Justice, we examine the impact of local corruption on firms’ debt maturity structure while exploring both demand-side and supply-side explanations. Our results support the demand-side story and indicate that firms in high corruption areas utilize less short-term debt to mitigate liquidity and refinancing risks. Consistent with this, we find the effect is more pronounced among firms with smaller size, lower asset redeployability, and higher volatility. Our findings remain robust to the inclusion of an array of controls expected to influence debt maturity preferences as well as time, industry, and state fixed effects. Moreover, a seemingly unrelated regression approach, instrumental variables regression, propensity score matching, placebo analyses, and alternative corruption measures corroborate our findings. Altogether, our results indicate that firms alter their debt maturity choices in response to local corruption to limit refinancing risk and the uncertainty created by corrupt government officials.

Board composition and value relevance of Ghanaian firms: a seemingly unrelated regression approach

PurposeThe purpose of this study is to examine the connection between board composition and value relevance of financial information in Ghana.Design/methodology/approachThe study uses a panel data of 144 firm-year observations of listed firms in Ghana.FindingsThe study finds that a higher fraction of independent directors is associated with lower firm value. The study further finds that board size is positively related to firm value, whereas duality is negatively associated with firm value.Practical implicationsThe practical implication of this paper is that investors and regulators should be mindful that specifying governance composition should not only be based on “so-called” codes of best practices but also the level of the country's or the sector's development and local institutional structures.Originality/valueThis study uses five different measurements of market share and considers the impact of the provision of the Code of Best Practices in Ghana.

Implications of Public Corruption for Local Firms: Evidence from Corporate Debt Maturity

Using political corruption conviction data from the U.S. Department of Justice, we examine the impact of local corruption on firms’ debt maturity structure while exploring both demand-side and supply-side explanations. Our results support the demand-side story and indicate that firms located in high corruption areas utilize less short-term debt to mitigate liquidity and refinancing risks. Consistent with this, we find the effect is more pronounced among firms with smaller size, lower asset redeployability, and higher volatility. Our findings remain robust to the inclusion of an array of controls expected to influence debt maturity preferences as well as time, industry, and state fixed effects. Moreover, a seemingly unrelated regression approach, instrumental variables regression, propensity score matching, and placebo analyses corroborate our findings. Altogether, our results indicate that firms alter their debt maturity choices in response to local corruption to limit refinancing risk and the uncertainty created by corrupt government officials.

Top management service commitment and new product development in manufacturing firms: the moderating role of dysfunctional competition

PurposeThis paper aims to investigate how top management service commitment (TSC) affects two dimensions of new product development (NPD), speed and product innovativeness, and to examine how dysfunctional competition moderates the effects in emerging economies.Design/methodology/approachData were collected from 151 high-tech manufacturing firms in China. In one firm, two different top managers were surveyed to reduce the common method variance. The authors used the seemingly unrelated regression approach to test the hypotheses.FindingsFirst, TSC negatively influences product innovativeness, an effect that dysfunctional competition attenuates. Second, despite not being significantly positive as hypothesized, the direct effect of TSC on NPD speed remains positive when dysfunctional competition is high rather than low. Third, the findings reveal that product innovativeness increases firm performance, but NPD speed shows no similar effect.Practical implicationsFirst, top managers should pay attention to the synergistic effect between industrial services and product businesses. Second, manufacturing firms in developing countries need to implement servitization when facing unlawful competitive behaviors.Originality/valueIn literature, the effect of industrial services on NPD is unclear. The present study enriches literature by connecting servitization with NPD and by focusing on the importance of top managers to the implementation of servitization. In addition, the authors extend the servitization literature to emerging economies and thereby provide significant insights into this context.

Forecasting and Mapping Coffee Borer Beetle Attacks Using GSTAR-SUR Kriging and GSTARX-SUR Kriging Models

The research aimed to use Generalized Space Time Autoregressive (GSTAR) and GSTARX modeling with the Seemingly Unrelated Regression (SUR) approach and combine them with the Kriging interpolation technique in an unobserved location. The case study was coffee borer beetle forecasting in Probolinggo Regency, East Java, Indonesia, with Watupanjang Village as the unobserved location. The results show that GSTAR-SUR Kriging and GSTARX-SUR Kriging models can predict coffee borer beetle attacks in unobserved areas with high accuracy. It is indicated by the Mean Absolute Percentage Error (MAPE) values of less than 10%. The addition of exogenous variables (rainfall) into the model is proven to improve the accuracy of the model. The Root-Mean-Square Error (RMSE) value of the GSTARX-SUR Kriging model is smaller than the GSTAR-SUR Kriging model. The structure of the model produced from the research, GSTARX-SUR (1,[1,12])(10,0,0), can be used as a reference in modeling coffee borer beetle attacks in other regencies. Map of forecasting coffee borer beetle attack shows that the spread of coffee borer beetle attack is spatial clustering with the attack center located in the eastern region of Probolinggo Regency.

DOES INFLATION ON ADMINISTERED PRICES AND VOLATILE FOODS COMMODITIES REDUCE THE HOUSEHOLDS WELFARE IN ACEH, INDONESIA?

High inflation is closely related to poverty. Inflation for volatile food is one of the causes of decreasing in household welfare. Volatile food commodities such as; rice, meat, fish, red chili, and shallot contributed to the inflation in the last three years. Likewise, administered price commodities such as LPG (liquefied petroleum gas), electricity, gasoline and water also contributed to high inflation. This study analyzes the effect of inflation on commodity-based welfare by analyzing the elasticity of demand for these commodities. The data used are cross section data obtained from the 2018 National Social Economic Survey (Susenas) of Aceh. The model used is the Almost Ideal Demand System (AIDS) model regressed with the Seemingly Unrelated Regression (SUR) approach. The results show that that most of the coefficient of the price has a negative and significant effect. The coefficient is used to calculate the elasticity of price variables, income elasticity, family size elasticity and education elasticity as control variables. The elasticity results indicates that prices greatly affect the decline in household welfare, displayed by the elastic value of demand for administrated and volatile food commodities while income elasticity, family size elasticity, and education elasticity shows an inelastic value. Therefore, it is recommended for Bank Indonesia and the government (in this case the Regional Inflation Control Team) to continue to pursue a commodity-based inflation control policy in Aceh. It is also necessary for the government to encourage more superior commodities, especially for volatile food commodities such as rice, meat, fish, red chili, and shallot. Producing more of the volatile food commodities will be important to maintain the price and quantity of food. In addition, the government must also provide symmetrical information about developments and plans to increase prices, thus not to cause excessive inflation expectations.

Sistemas de ecuaciones de altura-diámetro-edad para Pinus arizonica Engelmann y Pinus durangensisMartínez en rodales mezclados de Durango, México

<strong>Introduction:</strong> Total height (H) and diameter at breast height (DBH) are important variables in forest inventory and they are the basis for growth and yield systems. <br/> <strong>Objective:</strong> To generate three prediction and projection equation systems for Pinus arizonica Engelmann (Pa) and Pinus durangensis Martinez (Pd) in mixed stands in Durango, Mexico.<br/> <strong>Materials and methods:</strong> The outside-bark DBH equations as functions of the inside-bark DBH were developed and the H-DBH relationship was extended to three relationships with the use of age (A): H-DBH, H-A and DBH-A. The equation systems of H-DBH-A were developed from a database of 46 and 66 stem analysis trees with 601 and 760 longitudinal measurements of Pa and Pd, respectively. The equations were fitted with apparently unrelated regression and Dummy variables approach with common and specific parameters.<br/> <strong>Results and discussion:</strong> The relationships showed significant accuracy in the assessed fitting statistics (adjusted coefficient of determination, root mean square error, Akaike's information criterion, standard error of the estimate and bias). The inverse equations of the three relationships formed a global system of prediction and projection equations.<br/> <strong>Conclusions:</strong> The equations are useful for predicting and projecting H and DBH and they can be used as input variables in growth and yield models.

Energy consumption and financial development indicators nexuses in Asian economies: a dynamic seemingly unrelated regression approach.

In recent times, financial development and industrial progression accrue energy demand. Therefore, the present research is investigating the nexuses of energy consumption-financial development indicators for 32 Asian economies including the FDI, economic growth, and urban sprawl. The long-run marginal impacts and causal linkage are estimated through the dynamic seemingly unrelated regression and the heterogeneous causality respectively. The estimates infer that financial development indicators are deteriorating the energy consumption in the Asian region, while both FDI and urban sprawl accrue energy consumption. However, economy-wise estimates infer the heterogeneous impacts on energy consumption. Heterogenous causality infers a bidirectional causality among the financial development indicators and energy consumption. There is a need to devise the energy policies related to the financial sector for sustainable usage energy and a clean environment.

Efficient Estimation of Interval-Valued Symbolic Data Regression Model

In the last two decades, regression analysis with interval-valued type data has received more and more attention. For the interval-valued symbolic data regression, the Minmax method and the center and range (CR) method are two widely used popular estimating approaches. In this paper, to improve the estimating eciency of these two estimating methods, seemingly unrelated regression approach has been applied to take account of the dependence information of two regression models of the Minmax method or the CR method. Finally, real data sets are analysed to examine the performance of our proposed procedure.

The Impact of Thailand’s Openness on Bilateral Trade between Thailand and Japan: Copula-Based Markov Switching Seemingly Unrelated Regression Model

The purpose of this paper is to analyze the impact of trade openness and the factors based on the gravity model on the bilateral trade flows between Thailand and Japan. The factors consist of GDP, distance, trade openness, and exchange rate. Bilateral trade is composed of two flows: Thailand’s export flow to Japan, and Thailand’s import flow from Japan. The specified gravity equations are estimated by Copula-based Markov switching seemingly unrelated regression approach. The best-fitting model is chosen based on the lowest Akaike information criterion (AIC) and Bayesian information criterion (BIC). The Normal and Student’s t distributions are for Thailand’s export equation and Thailand’s import equation, respectively. The Student’s t copula is applied for joint distribution. Analyzing the bilateral trade flow is separated into two situations, namely the high and the low growth markets. Empirical results show that distance provides a positive effect on the export in a high growth regime, but a negative impact on the export in a low growth regime. As for Thailand’s import flow, all variables, but especially trade openness, provide strong evidence supporting significance for both regimes. For the GDPs of both Thailand and Japan, trade openness and the exchange rate increase import flow in a high growth market. Meanwhile, the exchange rate decreases import flow in a low growth market. The Markov Switching Probability Estimation notes that Thailand’s trading with Japan is mostly in the fast-growing market.

Weather and Crop Management Impact on Crop Yield Variability

This research is primarily designed to examine crop yield variation due to change in weather pattern and crop management activities by exploring a comprehensive list of factors (e.g. environmental, economic etc.). Given that existing literature indicates significant effects when farmland value is regressed on weather variables, a natural question is to ask whether major agricultural crop yields responds to change in historical weather pattern. To answer this question, this study relies on a state level panel dataset including agricultural and high-resolution weather data covering the period 1997-2018. Using a Seemingly Unrelated Regression (SUR) approach, this study estimates how crop spatial distribution patterns have impacted crop yield variation in response to weather in United States Greater Midwest region. Key findings indicate that changes in crop management activities correspond closely to estimate of both crop price and weather effects. Additionally, corn yield response to weather change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Further, revenue of corn, soybeans, wheat and their respective lagged yields have positive and significant effect to respective crop yields. Finally, a major crop yield does vary across region due to variation of crop prices, precipitation and temperature. These findings have useful implications for agriculture sector on how historical weather trends have affected crop yield and distribution pattern.

Are all tourism markets equal? Linkages between market-based tourism demand, quality of life, and economic development in Hong Kong

Tourism markets are heterogeneous, and their performance and effects can be better understood when considered separately. This paper investigates the linkages between tourism demand from several markets and quality of life, using Hong Kong as a case of study. The literature has, initially only considered a unilateral relationship running from aggregate tourism development to residents' quality of life, and a bilateral connection has only recently been recognized. The study contributes to the literature by considering a market-segmented (mainland China, Japan, the U.S., and other markets) approach to tourism demand, using a relatively underemphasized objectively-based method, and by providing building blocks for theoretical propositions. The methodology consists of unit root and cointegration testing, together with the application of the Three-Stage Least Squares method with the Seemingly Unrelated Regression approach on time-series data. The identified market-based differences can help academia and industry in better understanding the diverse markets and building a competitive edge.

Chief executive officer compensation, firm performance, and strategic coopetition: A seemingly unrelated regression approach

Coopetition denotes the simultaneous cooperation and competition in a business relationship and is broader in depth and width than competition. This pioneering comparative study employs a seemingly unrelated regression system to investigate the impact of peer‐pay bias and pay‐for‐relative performance upon the highly controversial chief executive officer (CEO) pay. The analysis of the 21 Dow–Jones firms from 1992 to 2013 shows that the pay‐for‐performance relationship is contingent on the fit between CEO's strategic decisions and firm's core competency. The CEO pay is driven by the intensification of firm coopetition. We contribute to executive compensation, corporate strategy, and econometric methods.

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.