Simultaneous Equation Bias Research Articles

Macroeconomic Impact of Value Added Tax in Nepal: A 2SLS and 3SLS Approach

The study’s aim to evaluate the impact of VAT on macroeconomic variables (TCON, GDP, Import (M) and GOVEXP) and the reverse effects of Macro variables on VAT. This study included macroeconomic development variables such as GDP, GDP (-1), VAT, remittance (REM), total consumption (TCON), export (X), import (M), gross fixed capital formation (GFCF), bank rate (BRATE), trade openness (TOPEN), government expenditure (GOVEXP) and one period lagged government expenditure (GOVEXP (-1)). However, this study has been enhanced over previous analyses by incorporating 45 years of nominal data from 1974/1975 to 2018/19. It examines the connection between VAT and significant macroeconomic variables such as GDP, GDP (-1), REM TCON, X, M, GFCF, BRATE, TOPEN, GOVEXP and GOVEXP (-1). To address the challenges of simultaneous equation bias and inconsistent findings, this study utilized the two-stage least squares (2SLS) and three-stage least squares (3SLS) methodologies to assess the impact of VAT on macroeconomic variables. The findings of the study are that value-added tax (VAT) negatively impacts TCON. VAT positively and significantly impacts on GDP, import(M), and GOVEXP. The study revealed that while TOPEN negatively affected Nepal’s GDP, GOVEXP, GFCF, and X had a significant and positive influence on GDP.

A learning by doing multiplier accelerates the transition to photovoltaic cells

Abating emissions of carbon dioxide depends in part on how quickly the levelized cost of electricity (LCOE) from photovoltaic cells (PV) achieves grid parity without policy interventions. Reaching this threshold is accelerated by learning by doing, which reduces the LCOE generated by PV. The resultant cost reduction generates a positive feedback loop and increases the demand for PV; but previous analyses ignore this feedback and therefore overlook a critical learning by doing multiplier effect, in which increasing the cumulative production of PV modules lowers their price, and lower PV module prices increase purchases of PV modules, which increases cumulative production of PV modules, and so on. We quantify the learning by doing multiplier effect with a cointegrating vector autoregression (CVAR) model that captures the simultaneous relation between the price for and cumulative production of PV modules. The learning by doing multiplier effect amplifies the static effects of learning by nearly a factor of ten and eliminates the simultaneous equation bias in previous estimates of unidirectional learning curves. This multiplier effect enhances the ability of policies, such as a carbon tax, to lower the costs of PV, increase cumulative production, and lower carbon emissions. Together, these results suggest that grid parity is closer than indicated by unidirectional learning curves.

Factors Affecting Employment Opportunities to Manufacturing Sector of Nepal

Nepalese manufacturing sector is not properly developed. However, manufacturing sector provides wide employment opportunities to people. Therefore, the main purpose of this study is to investigate the factors affecting employment opportunities in Nepalese manufacturing sector. This paper has employed two stage least square (2SLS) method using the time series macroeconomic data. The 2SLS method has been used to avoid the simultaneous equation bias. Manufacturing employment is explained variable and real foreign direct investment, manufacturing gross domestic product, NEPSE index and government expenditure in manufacturing sector are considered as explanatory variables. The 2SLS results have confirmed that foreign direct investment flows, capital market development, government expenditure and real GDP are positive and significant factors which contribute to expand the employment opportunities in manufacturing sector of Nepal. Therefore, Government of Nepal rise the expenditure in manufacturing sector as well as others infrastructure development to increase the flows of foreign capital in manufacturing sector to generate the employment opportunities. Furthermore, government of Nepal focus to develop financial markets for capital creation which leads economic growth as well as employment opportunities.

Confirming Anomalies

A procedure confirms whether a return-factor correlation is anomalous or results from endogenous simultaneous-equations bias. The identification strategy sorts the cost of capital components for instruments. In the first stage, the initially found factors are regressed on cost instruments. In the second stage, a confirmed anomaly has predicted value significant in returns and exogenous. Taxes, depreciation and capital structure are strong instruments, affecting 1980–2017 quarterly U.S. stock returns. Size, value and profitability decisions are significant in instruments. Returns increase in fitted profits, but not small size. Actual and predicted values have weaker correlation with returns over time.

Profitability, capital, and risk in US commercial and savings banks: Re-examination of estimation methods

This study compares the relationships between the three main bank variables i.e., profitability, capital, and risk of US commercial and savings banks for the period 1995Q1-2015Q4. As the literature analyzes the relationship between these variables in pairs, thus suffering from an 'omitted variable bias' and a 'simultaneous equations bias', we examine whether these biases are statistically significant. We compare the common methodology of a three two-equation system with both a three-equation system and three separate OLS regressions. While there are significant differences in the coefficients of the three main variables within the sample period, we could not find substantial differences in out-of-sample forecast estimates.

The Determinants of Pakistan Exports of Textile: An Integrated Demand and Supply Approach

The determinants of demand and supply of textile and clothing exports of Pakistan are examined for seven major trading partners (US, UK, Canada, Italy, France, Japan and Spain) over the period 1972 to 2013. The simultaneous equation model is estimated by Generalised Method of Moment to handle simultaneous equation bias and for consistent and more precise estimates classical Empirical Bayes technique is applied. The results reveal that income of trading partners and devaluation policy has important and significant role in explaining exports performance of textile and clothing of Pakistan. As regards the supply side, the relative prices and capacity variable are important in determining the textile and clothing exports, however, the real wages have significant but small effect on textile and clothing exports supply. The removal of quantitative restrictions fails to provide incentives to the suppliers. The high income elasticity for the demand suggests that focus should be on raising the factors which can help in expansion of textile and clothing products in local market and marked countries. Keywords: Textile and Clothing Exports of Pakistan, Simultaneous Equations, Real Effective Exchange Rate, Agreement on Textile and Clothing

Bias correction through filtering omitted variables and instruments

This paper proposes a combination of the particle-filter-based method and the expectation-maximization algorithm (PFEM), in order to filter unobservable variables and hence, to reduce the omitted variables bias. Furthermore, I consider as an unobservable variable, an exogenous one that can be used as an instrument in the instrumental variable (IV) methodology. The aim is to show that the PFEM is able to eliminate or reduce both the omitted variable bias and the simultaneous equation bias by filtering the omitted variable and the unobserved instrument, respectively. In other words, the procedure provides (at least approximately) consistent estimates, without using additional information embedded in the omitted variable or in the instruments, since they are filtered by the observable variables. The validity of the procedure is shown both through simulations and through a comparison to an IV analysis which appeared in an important previous publication. As regards the latter point, I demonstrate that the procedure developed in this article yields similar results to those of the original IV analysis.

The Compensation and Benefits of Private University and College Presidents

This study examines the determinants of the salaries of private college and university presidents. OLS estimates suggest that institutional size, performance and prestige are linked to presidents’ compensation. Pay is for performance. Externally recruited presidents are paid more than those promoted from inside, which tends to confirm the relationship between pay and performance. Non-denominational institutions tend to pay more than religiously affiliated ones. There is some evidence that large class sizes and low alumni giving rates are negatively associated with compensation. The impact of tenure is positive and significant, but its magnitude increases greatly if a quadratic term is added. In order to deal with potential simultaneous equations bias, the model was re-estimated with two-stage least squares. Using this method, the impact of enrollment on earnings rises and the effect of a peer assessment index on earnings is largely unchanged. The impact of various school characteristics on longevity as president is also investigated. Probit models indicate that the acceptance rate is negatively associated with the probability of remaining in office.

The Impact of Union Corruption on Union Membership

This paper examines the relationship between union corruption actions and union membership. State-level data from the Office of Labor-Management Standards, and other sources, are utilized over two study periods (1974-2000 and 2001- 2008) to test three hypotheses, including the union corruption hypothesis, as pos­sible explanations for the decline in union membership in the United States over time. Although our initial findings suggest a negative relationship exists between union corruption and membership, after removing the possibility of simultaneous equations bias, we find that changes in corruption do not influence changes in union membership in our sample.

A Comparison of Alternative Estimators of Macro-Economic Model of Ethiopia

During the past 5 decades a number of econometric techniques were developed and applied to a variety of econometric relationships to deal with the problem of single equation estimation as well as simultaneous equations bias. These days, such methods have very wide applications especially in more developed countries. However, there has been very little attempt to apply these techniques to empirical relationships describing the macro-economic sector of developing countries in general and Ethiopia in particular. In this study, a small macroeconometric model of Ethiopia is used to identify the best estimation techniques that will produce accurate forecast of the economy of Ethiopia. Six econometric methods were considered. The prediction accuracy of these estimators was examined using time series data covering the period 1970 to 2004. The results indicated that considerable gain in forecasting accuracy can be achieved by using 2SLSAUT01 and 2SLSAUT02 than simple ordinary least squares or two stage least squares to estimate macro-economic models. Key Words: Econometric Techniques, Econometric Models, Ethiopia, Prediction

Mechanistic-Empirical IRI Model Accounting for Potential Bias

The roughness prediction models in the International Roughness Index (IRI) currently incorporated into the Mechanistic-Empirical Pavement Design Guide (M-E PDG) have been developed by means of ordinary least squares (OLS). However, some of the variables used in predicting future IRI were previously estimated by means of separate performance models. This could cause bias because of the correlation between the previously estimated distress types and unobserved components on the IRI model. The bias can be corrected by considering additional variables that are correlated with the distress types causing the bias, thus eliminating the correlation to the unobserved terms in the model. Bias in the IRI model can also be generated by unobserved factors not included in the model. If these factors are section-specific, the bias can be removed considering variations in the performance history of different pavement sections. The writers have used updated Long-Term Pavement Performance (LTPP) data consistent with the data set originally used to fit the M-E IRI model for flexible pavements over thick granular bases contained in the M-E PDG. The data were then used in modeling IRI by means of OLS and instrumental variable (IV) regressions analyzing the data as pooled and as a panel data set (by random-effects, fixed-effects, and joint random-effects approach) to check for possible bias in the model. It was found that the current IRI model, as estimated by OLS, exhibits several types of biases attributed to heterogeneity and incorrect assumptions in the modeling process. It was identified that the preferred IRI model was the joint random-effects approach and, therefore, the model parameters were estimated by correcting the omitted-variable bias and simultaneous-equation bias. Estimating the model by accounting for possible bias in the data indicated considerable changes in the effects of different parameters affecting IRI through time, mainly rutting of the pavement structure.

When Are Supply And Demand Determined Recursively Rather Than Simultaneously?

When supply and demand are recursive, with uncorrelated cross-equation errors, least-squares estimation has no simultaneous-equation bias. Supply to a daily fish market is determined by the previous night's catch; hence this would appear to be a good example of a recursive market. Despite this, data from the Fulton fish market are treated in the literature, without adequate explanation, as coming from a market in which price and quantity are determined simultaneously. We provide the missing explanation, and in doing so reveal some issues about simultaneity that deserve better coverage in our textbooks and fuller consideration by applied econometricians.

Lifestyles, demographics, dietary behavior, and obesity: a switching regression analysis.

OBJECTIVES; To investigate the effects of lifestyles, demographics, and dietary behavior on overweight and obesity. Continuing Survey of Food Intakes by Individuals 1994-1996, U.S. Department of Agriculture. We developed a three-regime switching regression model to examine the effects of lifestyle, dietary behavior, and sociodemographic factors on body mass index (BMI) by weight category and accommodating endogeneity of exercise and food intake to avoid simultaneous equation bias. Marginal effects are calculated to assess the impacts of explanatory variables on the probabilities of weight categories and BMI levels. Weight categories and exercise are found to be endogenous. Lifestyle, dietary behavior, social status, and other sociodemographic factors affect BMI differently across weight categories. Education, employment, and income have strong impacts on the likelihood of overweight and obesity. Exercise reduces the probabilities of being overweight and obese and the level of BMI among overweight individuals. Health education programs can be targeted at individuals susceptible to overweight and obesity. Social status variables, along with genetic and geographic factors, such as region, urbanization, age, and race, can be used to pinpoint these individuals.

LIMIT THEORY FOR COINTEGRATED SYSTEMS WITH MODERATELY INTEGRATED AND MODERATELY EXPLOSIVE REGRESSORS

An asymptotic theory is developed for multivariate regression in cointegrated systems whose variables are moderately integrated or moderately explosive in the sense that they have autoregressive roots of the form ρni = 1 + ci/nα, involving moderate deviations from unity when α ∈ (0, 1) and ci ∈ ℝ are constant parameters. When the data are moderately integrated in the stationary direction (with ci < 0), it is shown that least squares regression is consistent and asymptotically normal but suffers from significant bias, related to simultaneous equations bias. In the moderately explosive case (where ci > 0) the limit theory is mixed normal with Cauchy-type tail behavior, and the rate of convergence is explosive, as in the case of a moderately explosive scalar autoregression (Phillips and Magdalinos, 2007, Journal of Econometrics 136, 115–130). Moreover, the limit theory applies without any distributional assumptions and for weakly dependent errors under conventional moment conditions, so an invariance principle holds, unlike the well-known case of an explosive autoregression. This theory validates inference in cointegrating regression with mildly explosive regressors. The special case in which the regressors themselves have a common explosive component is also considered.

Social class, family background, and intergenerational mobility

This research examines the various approaches taken by economists and sociologists for analyzing intergenerational mobility. Social mobility models based on social classes arising from an occupational classification scheme are analysed. A test for the statistical validity of classification schemes is proposed and tested using Danish sample survey data that was first collected in 1976 and augmented in 2000. This is referred to as a homogeneity test and is a likelihood ratio test of a set of linear restrictions which define social classes. For Denmark it is shown that this test fails for an Erikson–Goldthorpe classification system, raising doubts about the statistical validity of occupational classification systems in general. We also estimate regression models of occupational earnings, household earnings, and educational attainment using family background variables as covariates controlling for unobservables, measurement error, and simultaneous equation bias. In these models homogeneity tests are also rejected. We conclude from these results that the individual's family background has a small but significant impact on lifetime chances which is not captured by the Erikson–Goldthorpe classification scheme.

The impact of welfare reform on insurance coverage before pregnancy and the timing of prenatal care initiation.

This study investigates the impact of welfare reform on insurance coverage before pregnancy and on first-trimester initiation of prenatal care (PNC) among pregnant women eligible for Medicaid under welfare-related eligibility criteria. We used pooled data from the Pregnancy Risk Assessment Monitoring System for eight states (AL, FL, ME, NY, OK, SC, WA, and WV) from 1996 through 1999. We estimated a two-part logistic model of insurance coverage before pregnancy and first-trimester PNC initiation. The impact of welfare reform on insurance coverage before pregnancy was measured by marginal effects computed from coefficients of an interaction term for the postreform period and welfare-related eligibility and on PNC initiation by the same interaction term and the coefficients of insurance coverage adjusted for potential simultaneous equation bias. We compared the estimates from this model with results from simple logistic, ordinary least squares, and two-stage least squares models. Welfare reform had a significant negative impact on Medicaid coverage before pregnancy among welfare-related Medicaid eligibles. This drop resulted in a small decline in their first-trimester PNC initiation. Enrollment in Medicaid before pregnancy was independent of the decision to initiate PNC, and estimates of the effect of a reduction in Medicaid coverage before pregnancy on PNC initiation were consistent over the single- and two-stage models. Effects of private coverage were mixed. Welfare reform had no impact on first-trimester PNC beyond that from reduced Medicaid coverage in the pooled regression but separate state-specific regressions suggest additional effects from time and income constraints induced by welfare reform may have occurred in some states. Welfare reform had significant adverse effects on insurance coverage and first-trimester PNC initiation among our nation's poorest women of childbearing age. Improved outreach and insurance options for these women are needed to meet national health goals.

Instrumental variables estimation of stationary and non‐stationary cointegrating regressions

Summary Instrumental variables estimation is classically employed to avoid simultaneous equations bias in a stable environment. Here we use it to improve upon ordinary least-squares estimation of cointegrating regressions between non-stationary and/or long memory stationary variables where the integration orders of regressor and disturbance sum to less than 1, as happens always for stationary regressors, and sometimes for mean-reverting non-stationary ones. Unlike in the classical situation, instruments can be correlated with disturbances and/or uncorrelated with regressors. The approach can also be used in traditional non-fractional cointegrating relations. Various choices of instrument are proposed. Finite sample performance is examined.

Fee endogeneity, discretionary accruals and managerial incentive

Our study examines linkages between discretionary accruals, management ownership and remuneration and non-audit service (NAS) fees. All findings for our study are based on an extensive analysis of 351 Singapore publicly listed firms for the 2001 fiscal year period. Inferential statistics results using OLS and 2SLS reveals three key findings. First, there is a negative association between discretionary accruals and NAS fees. Second, managerial ownership positively affects the negative association between discretionary accruals and NAS fees. Third, this positive affect is weaker amongst firms with high accounting-based management remuneration. Our study also documents that when using single-equation estimates audit committee effectiveness is found to have a significant positive (negative) influence on audit coverage (purchase NAS fees). After controlling for fee endogeneity, however, the evidence shows that audit committee effectiveness is not associated with purchase of either audit or NAS fees. Findings from single-equation models of audit and NAS fees confirm prior research showing a knowledge spillover effect. Consistent with emerging literature, however, we show that when using simultaneous-equations the association between audit and NASs fees suffers from simultaneous-equation bias. Thus, consistent with Whisenant et al., (2003) we conclude there is no knowledge spillover between the two fees. Another key feature of this paper is we expand the very limited literature investigating linkages between audit committee effectiveness and the two fees. We document a failure to control for the feedback relationship between the two fee types is likely to produce spurious findings and inferences

Corporate Loan Spreads, Market Power, and the Default-Free Rate

The relation between corporate loan spreads and the default-free rate is investigated to determine whether lenders of corporate loans influence prices through increasing loan spreads as the default-free rate decreases, exploiting borrowers’ rate relief. The Loan Pricing Corporation DealScan database is employed to create large samples of revolving and term loans, which are independently estimated using techniques that overcome simultaneous equation bias. We find evidence to support the contention that lenders of revolving loans influence loan spreads through increasing commitment fees as the default-free rate decreases. We do not find any evidence that lenders of term loans influence loan spreads.

FIML Estimation of an Endogenous Switching Model for Count Data

This paper presents code for fitting a fiml endogenous switching poisson count model for cross-sectional data in stata 7: the espoisson command. the poisson process depends on an unobserved heterogeneity term, ξ; a set of explanatory variables, x; and an endogenous dummy, d. the endogenous dummy depends on an unobserved random term, ν. correlation between ξ and ν is allowed. if a model with exogenous d is fitted instead, correlation between ξ and ν will result in simultaneous equation bias. the endogenous switching model corrects this problem. after describing the underlying econometric theory behind the command, an example is discussed.