RIDGE ESTIMATORS FOR PROBIT REGRESSION: WITH AN APPLICATION TO LABOUR MARKET DATA

In this paper we propose ridge regression estimators for probit models since the commonly applied maximum likelihood (ML) method is sensitive to multicollinearity. An extensive Monte Carlo study is conducted where the performance of the ML method and the probit ridge regression (PRR) is investigated when the data are collinear. In the simulation study we evaluate a number of methods of estimating the ridge parameter k that have recently been developed for use in linear regression analysis. The results from the simulation study show that there is at least one group of the estimators of k that regularly has a lower mean squared error than the ML method for all different situations that have been evaluated. Finally, we show the benefit of the new method using the classical Dehejia and Wahba dataset which is based on a labour market experiment.     

The efficiency of the Scandinavian banking sector – a wavelet quantile regression analysis

In this article, the Scandinavian housing financing market is analysed in order to determine whether the interest rate price-discovery processes of Denmark, Norway and Sweden are efficient. Based on wavelet quantile regression analysis, we find systematic positive asymmetric price transmission (APT) inefficiencies. We conclude that there is a very high propensity for mortgage lenders to directly increase its customers’ mortgage interest rates subsequently to an increase in its borrowing costs. However, after a corresponding borrowing cost decrease, the same mortgage lenders are very slow to decrease its customers’ mortgage rates. These positive coefficients for so-called APT effects are found in all Scandinavian countries, even if the coefficients for Norway were not statistically significant. Wavelet quantile regression analysis, with a focus on the relevant higher percentiles, is easily motivated since the mortgage rates are adjusted very infrequently. Moreover, wavelet decomposition allows a robust analysis at different time frequency scales, while simultaneously controlling for nonstationary trends, autocorrelation and structural breaks. Except for the still positive but yet insignificant and inconclusive coefficients for Norway, the result is very clear-cut. Regardless of which wavelet scaling decomposition or quantile coefficient that is studied – positive APT effects are clearly identified and confirmed on the Scandinavian mortgage market.     

A procedure for adapting technological forecasting models

A simple procedure is presented for adapting available mathematical models for forecasting technological substitution. The procedure takes into consideration the strengths and weaknesses of the available models and the environmental interactions to identify a set of feasible alternative forecasts, from which a selection is to be made by the decision-maker based on judgement.     

Bootstrap methods for autocorrelation test with uncorrelated but not independent errors

By using bootstrap technique we investigate the properties of the Breusch [Breusch, T.S., 1978. Testing for autocorrelation in dynamic linear models. Australian Economic Papers 17, 334–355]–Godfrey [Godfrey, L.G., 1978. Testing for higher order serial correlation in regression equations when the regressors include lagged dependent variables. Econometrica 46, 1303–1310] autocorrelation tests in dynamic models with uncorrelated but not independent errors. In this paper we show that, under conditions when the errors are uncorrelated but not independent, even the best likelihood ratio test cannot achieve the asymptotic distribution under the null hypothesis of no autocorrelation. Standard bootstrap methods also fail to produce consistent results. To overcome this problem we applied several bootstrap testing methods for the same purpose and found the stationary bootstrap and Wild bootstrap with static model to perform adequately among the other bootstrap methods.     

Dynamic specification and misspecification in systems of demand equations: a testing strategy for model selection

The purpose of this study is to describe a misspecification testing strategy that is designed to ensure the appropriateness of the statistical assumptions underlying a system of equations. A systemwise test approach is used to test the statistical assumptions. The systemwise tests take into account information in, and interaction between, all equations in the system and can be used in a wide variety of applications where systems of equations are estimated. If the systemwise test leads to rejection, single equation F-test will then be used to help identify specific problems. The systemwise testing approach is illustrated by modelling Swedish consumer demand for milk. The example illustrates how the approach can be used to solve issues regarding dynamic specification of models, structural change and other forms of model misspecification.     

On Liu estimators for the logit regression model

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.     

Iraq’s budgetary practices post US invasion: a critical evaluation

ABSTRACT

Although the steep decline in oil prices has inflicted havoc on Iraq’s public finances, critical analyses of the budgetary decisions and processes post-US invasion have uncovered other factors that have impeded Iraq’s economic progress. The authors evaluate Iraq’s budgets for the period 2003 through 2012 from three perspectives: legislative framework, revenue and expenditure, and monitoring. One of their primary findings is that Iraq has been operating at a surplus in excess of $85 billion. This finding contradicts officials who claim that Iraq has been operating at a large deficit. The authors explain why Iraq’s current budgetary practices of preparing, ratifying, executing and monitoring the country’s federal budget is fundamentally deficient, and much work is needed to reform its public financial management (PFM) system to bring it up to best international practices.     

Growth and Jobs in Developing Economies: Trends and Cycles

Open Economies Review - This paper investigates the relationship between economic growth and job creation in developing economies with a focus on low and lower middle-income countries along two...