Recent Submissions

  • Catani, Paul; Ahlgren, Niklas (Hanken School of Economics, 2016-06-15)
    In this paper we propose a combined Lagrange multiplier (LM) test for autoregressive conditional heteroskedastic (ARCH) errors in vector autoregressive (VAR) models by following a suggestion in Dufour et al. (2010) of replacing an exact Monte Carlo (MC) test by a bootstrap MC test when the model includes lags. The test circumvents the problem of high dimensionality in multivariate tests for ARCH in VAR models. It is computationally simple since it only requires computing univariate statistics. The bootstrap MC test is shown to be asymptotically exact. Monte Carlo simulations show that the test has good finite-sample properties. The test is robust against a non-normal error distribution, while other multivariate LM tests for ARCH suffer from size distortion. We present two financial applications of multivariate LM tests for ARCH to credit default swap (CDS) prices and Euribor interest rates. The results indicate that the errors are skewed and heavy-tailed, and that there are significant ARCH effects.
  • Gerkman, Linda; Ahlgren, Niklas (2011-06-01)
    In this article we introduce and evaluate testing procedures for specifying the number k of nearest neighbours in the weights matrix of spatial econometric models. The spatial J-test is used for specification search. Two testing procedures are suggested: an increasing neighbours testing procedure and a decreasing neighbours testing procedure. Simulations show that the increasing neighbours testing procedures can be used in large samples to determine k. The decreasing neighbours testing procedure is found to have low power, and is not recommended for use in practice. An empirical example involving house price data is provided to show how to use the testing procedures with real data.
  • Asafu-Adjaye, John (Svenska handelshögskolan, 2002)
    This paper investigates the effect of income inequality on health status. A model of health status was specified in which the main variables were income level, income inequality, the level of savings and the level of education. The model was estimated using a panel data set for 44 countries covering six time periods. The results indicate that income inequality (measured by the Gini coefficient) has a significant effect on health status when we control for the levels of income, savings and education. The relationship is consistent regardless of the specification of health status and income. Thus, the study results provide some empirical support for the income inequality hypothesis.
  • Ahlgren, Niklas (Svenska handelshögskolan, 2000)
    This paper is concerned with using the bootstrap to obtain improved critical values for the error correction model (ECM) cointegration test in dynamic models. In the paper we investigate the effects of dynamic specification on the size and power of the ECM cointegration test with bootstrap critical values. The results from a Monte Carlo study show that the size of the bootstrap ECM cointegration test is close to the nominal significance level. We find that overspecification of the lag length results in a loss of power. Underspecification of the lag length results in size distortion. The performance of the bootstrap ECM cointegration test deteriorates if the correct lag length is not used in the ECM. The bootstrap ECM cointegration test is therefore not robust to model misspecification.
  • Ahlgren, Niklas; Sjöö, Boo (Svenska handelshögskolan, 2003)
    This paper uses panel unit root and cointegration methods to test the stationarity of the premium on domestic investors’ A shares over foreign investors’ B shares and cointegration between the A and B share prices on the Chinese stock exchanges. We find that the A share price premium is nonstationary until 2001, when the A and B share markets were partially merged, and that the A and B share prices are cointegrated in the panel.Cointegration is more likely to be found for firms in the service sector and for firms that issued B shares recently.
  • Ahlgren, Niklas; Antell, Jan (Svenska handelshögskolan, 2009-06-11)
    Bootstrap likelihood ratio tests of cointegration rank are commonly used because they tend to have rejection probabilities that are closer to the nominal level than the rejection probabilities of the correspond- ing asymptotic tests. The e¤ect of bootstrapping the test on its power is largely unknown. We show that a new computationally inexpensive procedure can be applied to the estimation of the power function of the bootstrap test of cointegration rank. The bootstrap test is found to have a power function close to that of the level-adjusted asymp- totic test. The bootstrap test estimates the level-adjusted power of the asymptotic test highly accurately. The bootstrap test may have low power to reject the null hypothesis of cointegration rank zero, or underestimate the cointegration rank. An empirical application to Euribor interest rates is provided as an illustration of the findings.
  • Ahlgren, Niklas; Juselius, Mikael (Hanken School of Economics, 2009-05-13)
    Many economic events involve initial observations that substantially deviate from long-run steady state. Initial conditions of this type have been found to impact diversely on the power of univariate unit root tests, whereas the impact on multivariate tests is largely unknown. This paper investigates the impact of the initial condition on tests for cointegration rank. We compare the local power of the widely used likelihood ratio (LR) test with the local power of a test based on the eigenvalues of the companion matrix. We find that the power of the LR test is increasing in the magnitude of the initial condition, whereas the power of the other test is decreasing. The behaviour of the tests is investigated in an application to price convergence.