A new bandwidth selection method for the fuzzy regression discontinuity estimator is proposed. The method chooses two bandwidths simultaneously, one for each side of the cut-off point by using a criterion based on the estimated asymptotic mean square error taking into account a second-order bias term. A simulation study demonstrates the usefulness of the proposed method. (C) 2016 Elsevier B.V. All rights reserved.

Are all Japanese youth ready for the structural reforms proposed as a supply-side policy of Abenomics? To answer this question, we assess how well Japanese youth have coped with the labor market's long-term structural changes, induced primarily by deepening interdependence with emerging economies and rapid technological progress over the last three decades. We examine the role of educational upgrading on the labor-market outcomes of youth between the ages of 25 and 29, using six waves of micro data from the Employment Status Survey spanning from 1982 to 2007. The analysis demonstrates that the demand growth for skilled labor relative to unskilled labor has been met by the educational upgrading of youth through the expansion of tertiary education, including education in vocational schools. Youth left behind the trend of educational upgrading, however, have suffered significantly from decreasing employment opportunities and deteriorated working conditions. National Graduate Institute for Policy Studies (GRIPS), Roppongi 7-22-1, Minato-ku, Tokyo 106-8677, Japan; Graduate School of Economics, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Graduate School of Economics, Hitotsubashi University, Naka 2-1, Kunitachi-shi, Tokyo 186-8601, Japan. (C) 2015 Elsevier Inc. All rights reserved.

This article considers a single-equation cointegrating model and proposes the locally best invariant and unbiased (LBIU) test for the null hypothesis of cointegration. We derive the local asymptotic power functions and compare them with the standard residual-based test, and show that the LBIU test is more powerful in a wide range of local alternatives. Then, we conduct a Monte Carlo simulation to investigate the finite sample properties of the tests and show that the LBIU test outperforms the residual-based test in terms of both size and power. The advantage of the LBIU test is particularly patent when the error is highly autocorrelated. Furthermore, we point out that finite sample performance of existing tests is largely affected by the initial value condition while our tests are immune to it. We propose a simple transformation of data that resolves the problem in the existing tests.

This paper investigates an efficient estimation method for a cointegrating regression model with structural change. Our proposal is that we first estimate the break point by minimizing the sum of squared residuals and then, by replacing the break fraction with the estimated one, we estimate the regression model by the canonical cointegrating regression (CCR) method proposed by Park [Econometrica (1992) Vol. 60, pp. 119-143]. We show that the estimator of the break fraction has the same convergence rate as obtained in Bai, Lumsdaine and Stock [Review of Economic Studies (1998) Vol. 65, pp. 395-432] and that the CCR estimator with the estimated break fraction has the same asymptotic property as the estimator with the known break point. However, we also show that our method breaks down when the magnitude of structural change is very small. Simulation experiments reveal how the finite sample distribution approaches the limiting distribution as the magnitude of the break and or the sample size increases.

In this paper we propose residual-based tests for the null hypothesis of cointegration with a structural break against the alternative of no cointegration. The Lagrange Multiplier (LM) test is proposed and its limiting distribution is obtained for the case in which the timing of a structural break is known. Then the test statistic is extended to deal with a structural break Of unknown timing. The test statistic, a Plug in version of the test statistic for known timing, replaces the true break point by the estimated one. We show the limiting Properties of the test statistic under the null as well as the alternative. Critical values are calculated for the tests by simulation methods. Finite-sample simulations show that the empirical size of the test is close to the nominal one unless the regression error is very persistent and that the test rejects the null when no cointegrating relationship with a structural break is present. We provide empirical examples based on the present-value model, the term structure model, and the money-output relationship model.

We show an alternative representation for the asymptotic distributions of impulse responses in cointegrated VAR systems. Our representation has the advantage that the asymptotic variances are convergent at long horizons. (C) 2000 Elsevier Science S.A. All rights reserved.