Least Square Dummy Variable Research Articles

An Analysis of the Impact of Foreign Investment on Regional Disparities: A Case of Malaysia

Foreign Direct Investment (FDI) is said to boost the economic growth of the host country and FDI also is one of the factors that contribute to regional disparities because FDI typically tend to focus on the areas that offer economic advantages compared to those areas of backward regions. This study aimed to investigate the effect of FDI on economic development and regional disparities in a globalizing economy of Malaysia. It explores the proposition that regional disparities are linked to the FDI that come into the country. This study involved six areas of the Northern, Central, Eastern, Southern, Sabah and Sarawak Regions. The variables used involved data acquired from Bank Negara Malaysia Report, Ninth Malaysia Plan, Tenth Malaysia Plan, Labor Investigation Report, Department Of Statistics Malaysia, Malaysian Investment Development Authority (MIDA) and Economic Planning Unit (EPU) and the period covered was 28 years ranging from the year of 1980 to 2008. The analysis was conducted using classical production function which explained output as function to capital and labor and involved time series and cross section data which will be regressed with Least Square Dummy Variables (LSDV) Regression Model and Random Effects Model. It was found that FDI is positive and significantly related to GDP implying that FDI is enhancing economic growth and regions with higher level of FDI tend to have higher GDP. Since FDI focuses on the developed areas especially the central, northern and southern regions, thus this concentration will widen the regional disparities in Malaysia. These disparities has brought about the imbalances between the society with regards to poverty, manufacturing activities and many more.

Trade Globalization, Financial Globalization and Inequality Within South-East Europe and CIS Countries

This paper contributes to the empirical literature by investigating trade globalization and financial globalization as channels of inequality within South-East Europe and the Commonwealth of Independent States (CIS) countries from 1992 to 2007. In addition, the paper uses KOF (2010) index to measure the overall impact of globalization on income inequality in South-East Europe and the CIS countries. To overcome the limitations of the least squares dummy variables (LSDV) model, Parks method is used. The paper has two results. The first result is that both trade globalization and financial globalization deepen the income inequality within South-East Europe and the CIS countries. The second result is that the overall impact of globalization have adverse effect on inequality within South-East Europe and CIS countries from 1992 to 2007. These results support the hypothesis that globalization widens the income inequality within countries.

Crop diversification in India: a study of maize cultivation in Karnataka

Growing need of agricultural production has been greatly felt with the growth of population, not only for the sake of food security but also for providing employment. Crop diversification within the sector has also been noticed to a great extent. Of which, the growth of production of maize has registered at the highest with CAGR at 8.5 per cent in the last three decades. Using one way Least Squares Dummy Variable (LSDV) for twenty-seven districts over twelve years, present study explored that the introduction of new hybrid seed (HYV) is one of the most important factors for significant growth of maize crop in the state. Further, though the crop is suitable in the drier region, the role of timely rainfall is also found to have significant on the yield level.

Home Country Determinants of Outward FDI: A Study of Select Asian Economies

Since the early 1990s, developing countries have seen a rapid growth in their outward investments. The share of South, East and South-East Asia in global outward FDI has substantially increased in the last two decades. Due to the increasing importance of this region in global outward FDI, this paper attempts to examine the home country determinants of outward FDI in ten select economies of the region. With the help of panel data for the period 1991-2010, this paper models the role of home country “push” factors in promoting outward FDI. A fixed effects (Least Squares Dummy Variables (LSDV)) model is developed that captures market conditions, policy variables, economic variables and production factors. We have also used Principal Component Analysis to augment the model’s analytical richness. The results indicate that GDP and FDI openness are important home country factors affecting outward FDI. Countries with high GDP and a more liberal and open FDI policy have larger FDI outflows.

Superioridad relativa de los estimadores Kiviet y Blundell-Bond (GMM1) en paneles dinámicos. Un experimento Monte Carlo con muestras finitas

Given the widespread use of panel data in dynamic models, it is worth evaluating the performance of different estimators in finite samples in the presence of low and high persistence, with the latter being present in many macroeconomic series. This article analyzes the properties of the Least Square Dummy Variable (LSDV) estimators, Arellano-Bond Generalized Method of Moments Stage 1 (AB-GMM1), BBGMM1 (), AH (Anderson-Hsiao), and Kiviet using a Monte Carlo experiment. The results show that, in the presence of low persistence, the Kiviet estimator is the best performer based on the criteria of Root-Mean-Square Error (RMSE), bias and standard deviation. Meanwhile in the case of high persistence, the system estimator of Blundell and Bond (GMM1) is the best performing estimator against their rivals, followed by Kiviet estimator that exhibits good behavior, except in micropanels.

Response of residential electricity demand to price: The effect of measurement error

In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured. To address these issues, we estimate a dynamic partial adjustment model using the Kiviet corrected Least Square Dummy Variables (LSDV) (1995) and the Blundell–Bond (1998) estimators. We find that the long-term elasticities produced by the Blundell–Bond system GMM methods are largest, and that from the bias-corrected LSDV are greater than that from the conventional LSDV. From an energy policy point of view, the results obtained using the Blundell–Bond estimator where we instrument for price imply that a carbon tax or other price-based policy may be effective in discouraging residential electricity consumption and hence curbing greenhouse gas emissions in an electricity system mainly based on coal and gas power plants.

On the asymptotic [formula omitted]-test for large nonstationary panel models

The asymptotic t-test for the long-run average in a heterogeneous nonstationary panel model is derived. The asymptotics of the Least Squares Dummy Variable (LSDV) and of the Pooled-OLS (POLS) estimators for the slope parameter are studied under various circumstances (serial correlation, strong cross-sectional dependence in the errors and in the regressors and mixed stationary/nonstationary errors) and a modified estimator of the asymptotic variance is derived. The asymptotic variance is computed up to a simple transformation of the residual and no nuisance parameters need to be estimated. The resulting t-statistics are shown to have a standard normal limiting distribution. Asymptotic tests based on the standardized version of the t-statistic are shown to have good power properties, and the correct size, even for n as small as 25.

Regional integration and trade: A panel cointegration approach to estimating the gravity model

Using a panel data set of bilateral export flows from 12 European Union (EU) countries to 20 Organisation for Economic Co-operation and Development (OECD) trading partners over the period 1992–2003, a panel cointegration approach to estimating the gravity model is adopted to test for the significance of European regional integration. A comparison of the results indicates that a positive and significant coefficient estimate of the EU dummy variable is found for both the pooled ordinary least squares (POLS) estimator and the dynamic ordinary least squares (DOLS) estimator. The results, however, diverge once fixed effects are admitted into the model. The least squares dummy variable (LSDV) estimator suggests a small positive effect of EU integration on trade. In contrast, the dynamic LSDV estimator indicates that regional integration has a larger beneficial effect on trade. The results highlight the fundamental importance of properly accounting for endogeneity when evaluating trade policy effects.

The Global Financial Crisis and Sub‐Saharan Africa: The Effects of Slowing Private Capital Inflows on Growth*

Abstract: This paper uses the bias‐corrected least‐squares dummy variable (LSDV) estimator to examine the relationship between economic growth and four different types of private capital inflows (cross‐border bank lending, foreign direct investment (FDI), bonds flows and portfolio equity flows) on a sample of 15 selected sub‐Saharan African countries over the period 1980–2008. Our results show that FDI and cross‐border bank lending exert a significant and positive impact on sub‐Saharan Africa's growth, whereas portfolio equity flows and bonds flows have no growth impact. Our estimates suggest that a drop by 10 per cent in FDI inflows may lead to a 3 per cent decrease of income per capita growth in sub‐Saharan Africa, and a 10 per cent decrease in cross‐border bank lending may reduce growth by up to 1.5 per cent. Therefore, the global financial crisis is likely to have an important effect on sub‐Saharan Africa's growth through the private capital inflows channel.

Demand Side Factors Affecting the Inflow of Foreign Direct Investment to African Countries: Does Capital Market Matter?

This paper aims at providing empirical analysis of the demand side determinants of the inflow of Foreign DirectInvestment to African nations, with particular emphasis on stock market availability. Due to data heterogeneity,non-continuity and because the Hausman test favors it, cross section fixed effect Least Square Dummy Variable(LSDV) estimation technique is used. Natural resource, labor quality, trade openness, market accession andinfrastructure condition are found to have positive and significant effect. Availability of stock market has theexpected positive but insignificant effect. In search of possible explanation governments’ expenditure andprivate domestic investment are added to the regression equation and are found to have positive effect, ruling outthe possibility of crowding out effect. Stock markets in Africa are not structured in such a way that they cancontribute to attract FDI and hence policy makers should restructure capital markets to get the most out of them.The bottom line is, policy makers of those countries have a lot of demand side instruments under their discretionto attract FDI inflow.

The Effect of Capital Adequacy on Banks’ Performance: Evidence from Nigeria

This study estimates the effect of capital adequacy on bank earnings and profitability in Nigeria. Panel data are provided for a sample of 10 strong banks and 10 weak banks in the period 2000-2003 with the strong banks selected on the basis of the first 20 companies listed with the highest market capitalization. With the aid of a Least Square Dummy Variable (LSDV) model, the study found that bank earnings is invariants to factors such as bank assets and bank size but highly driven by liquidity and capital adequacy. The fixed effect model showed the distinction between strong and weak bank does not hold as differential intercept dummy shows that the effect of capital adequacy on bank performance is stronger for weak banks than for strong banks. The study concludes that consolidation exercise that reinforced the capital base of the banks from a minimum capital base of N2 billion to N25 billion was a step in the right direction and suggest that the need for effective regulatory framework in the management liquidity and bank capital to shore-up bank performance in Nigeria.

A longitudinal study on Australian online DVD pricing

PurposeThe purpose of this paper is to analyze the online DVD market in Australia, which has not been researched so far, and to examine whether the pricing patterns in this market exhibit any regularity consistent or inconsistent with research findings in other markets.Design/methodology/approachA longitudinal data set of 27,030 price observations were collected weekly over one year. Various statistical tests – in particular, a least‐squares dummy variable (LSDV) panel data model with serial correlation – were applied to the data.FindingsIn general, the online branches of multi‐channel retailers have higher average prices and standard deviations than pure internet retailers. Overall, market prices decrease over time significantly within the sample period – about 17.4 per cent decrease for all titles, however, with popular titles' prices decreasing faster than those of random titles. Furthermore, prices do not seem to converge between the two types of online retailers. For individual retailers, brand name effect seems to matter in the results, with a significant difference on prices.Research limitations/implicationsThis is an empirical study on a specific market. More data, testing and comparison are needed for any generalization of the findings whether they are consistent in the global sense.Practical implicationsOnline marketers of different types of retailers may need to reflect on their pricing policies whether their pricing strategies have any space for improvement on profitability.Originality/valueThis study investigates the price movement of the Australian online DVD market using data collected over a one year time span.

Ordinary Least Square Vs Fixed Effect Regression Model: Studi Empirik Determinan Kebijakan Dividen pada Perusahaan-Perusahaan yang Terdaftar di Bursa Efek Indonesia (BEI)

This research analyzes determinants of corporate dividend policy in Indonesia Stock Exchange (IDX). This research hypothesizes that four financial ratios, which are dividend yield, ROA (return on assets), leverage and PBV (price-to-book value ratio) are determinants of corporate dividend policy.Samples of 25 firms, which are included in many sectors, are all fulfilling data completeness criteria. Research periods are from 2002 until 2006. A balanced panel data study technique is employed to analyze determinants of corporate dividend policy in Indonesia Stock Exchange (IDX). There are two models to estimate regression model used in this research, that is usual Ordinary Least Square (OLS) regression model and the Fixed Effects (FE) or Least Squares Dummy Variable (LSDV) regression model.The study documented that dividend yield, return on assets and leverage have positive effect to dividend payment significantly based on OLS model. Otherwise FE model found dividend yield is the only variable that statistically significant influence dividend payment. The better model to predict determinants of corporate dividend policy is FE model. FE model has higher R-squared value and Durbin-Watson d value than OLS model. In addition, FE model can explain this issue clearly and specifically.Keywords: dividend policy, dividend yield, ROA, leverage, PBV.

New results for nonstationary panel regression

This article derives the limiting distributions of the Ordinary Least Squares (OLS) and Least Square Dummy Variable (LSDV) estimators in both spurious and cointegrated panel regressions. The limit theories employed in this article are different from those of Kao (1999) and Phillips and Moon (1999), in which the time dimension of the panel is fixed.

Privatization, Governance and Economic Development in Developing Countries

The study examined the impact of privatization on economic growth and income inequality in 82 developing countries between 1991 and 2002. Using the least squares dummy variable (LSDV) approach, we found that privatization did not have a significant impact on both economic growth and income inequality. However, good governance had a positive impact on economic growth and a negative impact on income inequality, while foreign direct investment (FDI) had a negligible impact on economic growth but a positive effect on income inequality. The findings of the study suggest that country-specific characteristics may be more important in promoting growth and reducing income inequality than any economic policy per se.

Light Rail Cost Functions and Technical Inefficiency

Light rail operating costs vary with a system's scale of operations, traffic density, vehicle and passenger outputs, and input prices. Previous attempts at estimating these cost relationships have been hampered by inadequate data and methodologies that restrict their functional forms, limit their output measures, omit factor prices, and fail to account for technical inefficiencies. With more data now available from an increased number of systems operating during longer time periods, new cost specifications that improve the precision and reduce the bias of cost estimates can be estimated. Here, light rail cost functions are estimated with 1994 to 2005 data for 21 U.S. light rail systems. The cost functions relate operating and maintenance costs to passenger and vehicle outputs, input prices, route densities, vehicle capacities, and latent cost inefficiencies. Four estimation methods are used: (a) iterative seemingly unrelated regression, (b) least-squares dummy variable, (c) maximum likelihood stochastic frontier, and (d) hierarchical Bayesian frontier models. Economies of size and density, input productivities, input substitution elasticities, and transit system inefficiencies are measured.

Estimation and Inference in Dynamic Unbalanced Panel-data Models with a Small Number of Individuals

This article describes a new Stata routine, xtlsdvc, that computes bias-corrected least-squares dummy variable (LSDV) estimators and their bootstrap variance–covariance matrix for dynamic (possibly) unbalanced panel-data models with strictly exogenous regressors. A Monte Carlo analysis is carried out to evaluate the finite-sample performance of the bias-corrected LSDV estimators in comparison to the original LSDV estimator and three popular N-consistent estimators: Arellano–Bond, Anderson–Hsiao and Blundell–Bond. Results strongly support the bias-corrected LSDV estimators according to bias and root mean squared error criteria when the number of individuals is small.

Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53–78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L‐F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199–225] are extended to higher‐order dynamic panel data models with general covariance structure. The focus is on estimation of both short‐ and long‐run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I–1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long‐run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross‐correlation patterns between countries are sometimes considerable.

Spurious regression and residual-based tests for cointegration in panel data

In the first half of the paper I study spurious regressions in panel data. Asymptotic properties of the least-squares dummy variable (LSDV) estimator and other conventional statistics are examined. The asymptotics of LSDV estimator are different from those of the spurious regression in the pure time-series. This has an important consequence for residual-based cointegration tests in panel data, because the null distribution of residual-based cointegration tests depends on the asymptotics of LSDV estimator. In the second half of the paper I study residual-based tests for cointegration regression in panel data. I study Dickey–Fuller (DF) tests and an augmented Dickey–Fuller (ADF) test to test the null of no cointegration. Asymptotic distributions of the tests are derived and Monte Carlo experiments are conducted to evaluate finite sample properties of the proposed tests.

Estimation and Inference of a Cointegrated Regression in Panel Data: A Monte Carlo Study

SYNOPTIC ABSTRACTThis paper studies the finite sample properties of the least squares dummy variable (LSDV) estimator and t-statistic in a cointegrated regression in panel data. Through Monte Carlo studies we find that both the LSDV estimator and the t-statistic have a small amount of bias, and the t-statistic diverges as the cross-sectional dimension increases. We also find that the bias-corrected LSDV estimator and the bias-corrected t-statistic do not reduce the magnitude of the bias problem.