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  • 1. Badunenko, Oleg
    et al.
    Fritsch, Michael
    Stephan, Andreas
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Allocative Efficiency Measurement Revisited: Do We Really Need Input Prices?2008In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 25, no 5, p. 1093-1109Article in journal (Refereed)
  • 2. Baum, Christopher F.
    et al.
    Caglayan, Mustafa
    Stephan, Andreas
    Jönköping University, Jönköping International Business School, JIBS, Economics. Jönköping University, Jönköping International Business School, JIBS, Accounting and Finance.
    Talavera, Oleksandr
    Uncertainty Determinants of Corporate Liquidity2008In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 25, no 5, p. 833-849Article in journal (Refereed)
    Abstract [en]

    This paper investigates the link between the optimal level of non-financial firms' liquid assets and uncertainty. We develop a partial equilibrium model of precautionary demand for liquid assets showing that firms alter their liquidity ratio in response to changes in either macroeconomic or idiosyncratic uncertainty. We test this hypothesis using a panel of non-financial US firms drawn from the COMPUSTAT quarterly database covering the period 1993–2002. The results indicate that firms increase their liquidity ratios when macroeconomic uncertainty or idiosyncratic uncertainty increases.

  • 3.
    Hatemi-J, Abdulnasser
    Jönköping University, Jönköping International Business School.
    Fiscal Policy in Sweden: Effects of EMU Criteria Convergence2002In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 19, no 1, p. 121-136Article in journal (Refereed)
  • 4. Mantalos, Panagiotis
    et al.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Bootstrap Methods for Autocorrelation Test with Uncorrelated but not Independent Errors2008In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 25, no 5, p. 1040-1050Article in journal (Refereed)
  • 5.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
    On ridge estimators for the negative binomial regression model2012In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 29, no 2, p. 178-184Article in journal (Refereed)
    Abstract [en]

    The negative binomial (NB) regression model is very popular in applied research when analyzing count data. The commonly used maximum likelihood (ML) estimator is very sensitive to highly intercorrelated explanatory variables. Therefore, a NB ridge regression estimator (NBRR) is proposed as a robust option of estimating the parameters of the NB model in the presence of multicollinearity. To investigate the performance of the NBRR and the traditional ML approach the mean squared error (MSE) is calculated using Monte Carlo simulations. The simulated result indicated that some of the proposed NBRR methods should always be preferred to the ML method.

  • 6.
    Månsson, Kristofer
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
    Kibria, B. M. Golam
    Department of Mathematics and Statistics, Florida International University, Miami, FL, USA.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
    On Liu Estimators for the Logit Regression Model2012In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 29, no 4, p. 1483-1488Article in journal (Refereed)
    Abstract [en]

    This paper introduces a shrinkage estimator for the logit model which is a generalization of the estimator proposed by Liu (1993) for the linear regression. This new estimation method is suggested since the mean squared error (MSE) of the commonly used maximum likelihood (ML) method becomes inflated when the explanatory variables of the regression model are highly correlated. Using MSE, the optimal value of the shrinkage parameter is derived and some methods of estimating it are proposed. It is shown by means of Monte Carlo simulations that the estimated MSE and mean absolute error (MAE) are lower for the proposed Liu estimator than those of the ML in the presence of multicollinearity. Finally the benefit of the Lie estimator is shown in an empirical application where different economic factors are used to explain the probability that municipalities have net increase of inhabitants.

  • 7.
    Månsson, Kristofer
    et al.
    Jönköping University, Jönköping International Business School.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
    Testing for nonlinear panel unit roots under cross-sectional dependency: with an application to the PPP hypothesis2014In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 38, p. 121-132Article in journal (Refereed)
    Abstract [en]

    In this paper we propose a number of nonlinear panel unit root tests that are robust to cross-sectional dependency. These tests may be used to test the null hypothesis of non-stationarity against the alternative that some or all of the time series in the system of equations follow a stationary exponential smooth transition autoregressive (ESTAR) process. In contrast to previous research we relax the assumption that the cross-correlation structure is driven by a common-factor and consider an endogenous correlation structure. Based on the size and power results from the Monte Carlo simulations we recommend using the Wald version of our cross-sectional dependent robust nonlinear panel unit root (CDR-NPU) method.

    Finally, in an empirical application we demonstrate that our more powerful nonlinear method, in contrast to previous methods, can provide support for PPP even in smaller samples. In consistency with the univariate tests in Bahmani-Oskooee et al. (2008) our CDR-NPU tests support the theory that less industrialized economies exhibit stronger and more distinct nonlinear adjustment patterns towards PPP.

  • 8.
    Schäfer, Dorothea
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Center for Family Enterprise and Ownership.
    Talavera, Oleksandr
    The University of Sheffield.
    Weir, Charlie
    The Robert Gordon University.
    Entrepreneurship, windfall gains and financial constraints: Evidence from Germany2011In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 28, no 5, p. 2174-2180Article in journal (Refereed)
    Abstract [en]

    We investigate the link between the propensity to become an entrepreneur and the exogenous release from financial constraints in Germany. This is defined in terms of the movement from employment to self-employment on receipt of a financial windfall. A theoretical framework developing Evans and Jovanovic (1989) is set up and tested with panel data from German households. The results show that financial constraints do exist given that individuals are more likely to start a personal business after receiving a windfall gain. The value of windfall gains has a significant but non linear effect on the decision to become self employed. The data reveal that differences in ability and income affect the change in employment status. We also report that there is no evidence that becoming self-employed involves the anticipation of windfall gains.

  • 9.
    Shukur, Ghazi
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
    A poisson ridge regression estimator2011In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 28, no 4, p. 1475-1481Article in journal (Refereed)
    Abstract [en]

    The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML) method. The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson ridge regression estimator (PRR) as a remedy to the problem of instability of the traditional ML method. To investigate the performance of the PRR and the traditional ML approaches for estimating the parameters of the Poisson regression model, we calculate the mean squared error (MSE) using Monte Carlo simulations. The result from the simulation study shows that the PRR method outperforms the traditional ML estimator in all of the different situations evaluated in this paper.

  • 10.
    Shukur, Ghazi
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
    On the median regression for SURE models with applications to 3-generation immigrants data in Sweden2011In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 28, no 6, p. 2566-2578Article in journal (Refereed)
    Abstract [en]

    In this paper we generalize the median regression method to be applicable to system of regression equations, in particular SURE models. Giving the existence of proper system wise medians of the residuals from different equations, we apply the weighted median regression with the weights obtained from the covariance matrix of the equations obtained from ordinary SURE method. The benefit of this model in our case is that the SURE estimators utilise the information present in the cross regression (or equations) error correlation and hence more efficient than other estimation methods like the OLS method. The Seemingly Unrelated Median Regression Equations (SUMRE) models produce results that are more robust than the usual SURE or single equations OLS estimation when the distributions of the dependent variables are not normally distributed or the data are associated with outliers. Moreover, the results are also more efficient than is the cases of single equations median regressions when the residuals from the different equations are correlated. A theorem is derived and indicates that even if there is no statistically significant correlation between the equations, using SUMRE model instead of SURE models will not damage the estimation of parameters.

  • 11. Sjölander, Pär
    A ridge bootstrap method for analyzing APT effects on the mortgage loan market2013In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 30, p. 844-855Article in journal (Refereed)
    Abstract [en]

    Significantly positive asymmetric price transmission (APT) effects are concluded on the Swedish mortgage loan market. This finding was established based on unique banking data in combination with our newly developed econometric method which is insensitive to the banks' variations in liquidity and capital costs. It is established that there is a higher propensity for the bank to rapidly and systematically increase its fixed mortgage interest rates for customers subsequently to an increase in its borrowing costs, compared with the propensity for the bank to decrease its customers' mortgage rates subsequently to a corresponding borrowing cost decrease.

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