Probit Models with Binary Endogenous Regressors

Sample selection and endogeneity are frequent causes of biases in non-experimental empirical studies. In binary models a standard solution involves complex multivariate models. A simple approximation has been shown to work well in bivariate models. This paper extends the approximation to a trivariate model. Simulations show that the approximation outperforms full maximum likelihood while a least squares approximation may be severely biased. The methods are used to estimate the influence of trust in the parliament and politicians on voting- propensity. No previous studies have allowed for endogeneity of trust on voting and it is shown to severely affect the results.endogeneity; multivariate probit; approximation; Monte Carlo simulation

Likelihood Ratio Testing for Cointegration Ranks in I(2) Models.

This paper presents the likelihood ratio (LR) test for the number of cointegrating and multi-cointegrating relations in the I(2) vector autoregressive model. It is shown that the asymptotic distribution of the LR test for the (multi-) cointegration ranks is identical to the asymptotic distribution of the much applied test statistic based on the Two-Step procedure in Johansen (1995), Paruolo (1996), and Rahbek, Kongsted, and Jørgensen (1999). By construction the LR test statistic is smaller than the non-LR test statistic from the Two-Step procedure as the latter ignores some of the restrictions concerning the hypothesis of I(2), and application of the LR test may change rank selection in empirical work. Based on a study of existing empirical applications and related Monte Carlo simulations we conclude that the LR test has much better size properties when compared to the Two-Step based test. Overall, we propose to use of the LR test for rank determination in I(2) analysis as the Two-Step based statistic was developed as a feasible approximation to the then unobtainable LR test.vector autoregression; error correction model; cointegration; I(2); likelihood ratio test; Monte Carlo; reduced rank; rank testing

Where did they go?

We study individual job-separations and their associated destination states for all individuals in the private sector in Denmark for the period 1980 to 1995 and account for the cyclical flows. We find that individual and workplace characteristics as well as business cycle effects are important in explaining the individual behaviour. In policy simulations we look at the impact on individual transitions. We find that structural and growth policies have different implications for the economy. Policy interventions with the purpose of preventing firm closures are argued to be inefficient.Business cycles; Job separations; Transition probabilities

Durability of air lime mortar

This contribution deals with the physical and chemical reasons why pure air lime mortars used in masonry of burned bricks exposed to outdoor climate have shown to be durable from the Middle Ages to our days. This sounds strange in modern times where pure air lime mortars are regarded as weak materials, which are omitted from standards for new masonry buildings, where use of hydraulic binders is prescribed.The reasons for the durability seam to be two:1. The old mortars have high lime contents.2. The carbonation process creates a pore structure with a fine pored outer layer and coarser pores inside. This difference in pore size will delay the capillary suction of rain from outside, while excess water inside can be sucked to the front and evaporate

Choosing the observational likelihood in state-space stock assessment models

Data used in stock assessment models result from combinations of biological, ecological, fishery, and sampling processes. Since different types of errors propagate through these processes it can be difficult to identify a particular family of distributions for modelling errors on observations a priori. By implementing several observational likelihoods, modelling both numbers- and proportions-at-age, in an age based state-space stock assessment model, we compare the model fit for each choice of likelihood along with the implications for spawning stock biomass and average fishing mortality. We propose using AIC intervals based on fitting the full observational model for comparing different observational likelihoods. Using data from four stocks, we show that the model fit is improved by modelling the correlation of observations within years. However, the best choice of observational likelihood differs for different stocks, and the choice is important for the short-term conclusions drawn from the assessment model; in particular, the choice can influence total allowable catch advise based on reference points.Comment: To be published in Canadian Journal of Fisheries and Aquatic Science

Plasmonic metagratings for simultaneous determination of Stokes parameters

Measuring light's state of polarization is an inherently difficult problem, since the phase information between orthogonal polarization states is typically lost in the detection process. In this work, we bring to the fore the equivalence between normalized Stokes parameters and diffraction contrasts in appropriately designed phase-gradient birefringent metasurfaces and introduce a concept of all-polarization birefringent metagratings. The metagrating, which consists of three interweaved metasurfaces, allows one to easily analyze an arbitrary state of light polarization by conducting simultaneous (i.e., parallel) measurements of the correspondent diffraction intensities that reveal immediately the Stokes parameters of the polarization state under examination. Based on plasmonic metasurfaces operating in reflection at the wavelength of 800 nm, we design and realize phase-gradient birefringent metasurfaces and the correspondent metagrating, while experimental characterization of the fabricated components convincingly demonstrates the expected functionalities. We foresee the use of the metagrating in compact polarimetric setups at any frequency regime of interest

An I(2) Cointegration Model With Piecewise Linear Trends: Likelihood Analysis And Application

This paper presents likelihood analysis of the I(2) cointegrated vector autoregression with piecewise linear deterministic terms. Limiting behavior of the maximum likelihood estimators are derived, which is used to further derive the limiting distribution of the likelihood ratio statistic for the cointegration ranks, extending the result for I(2) models with a linear trend in Nielsen and Rahbek (2007) and for I(1) models with piecewise linear trends in Johansen, Mosconi, and Nielsen (2000). The provided asymptotic theory extends also the results in Johansen, Juselius, Frydman, and Goldberg (2009) where asymptotic inference is discussed in detail for one of the cointegration parameters. To illustrate, an empirical analysis of US consumption, income and wealth, 1965 - 2008, is performed, emphasizing the importance of a change in nominal price trends after 1980.Cointegration, I(2); piecewise linear trends; likelihood analysis; US consumption