When estimating hedonic models of housing prices, the use of time series cross-section repeat sales data can provide improvements in estimator efficiency and correct for unobserved characteristics. However, in cases where serial correlation is present, the irregular timing of sales should also...

In this paper we explore the long term movement in the housing prices in select American cities. Using the monthly S&P/Case-Shiller Home Price Indices, we look at the stability of housing prices in 14 selected large American cities. We undertake the ADF (GLS) unit root test for the index in each...

We consider a new copula method for mixed marginals of discrete and continuous random variables. Unlike the Bayesian methods in the literature, we use maximum likelihood estimation based on closed-form copula functions. We show with a simulation that our methodology performs similar to the...

The time-series nature of mortality rates lends itself to processing through neural networks that are specialized to deal with sequential data, such as recurrent and convolutional networks. Although appealing intuitively, a naive implementation of these networks does not lead to enhanced...

This paper introduces a new multivariate model for time series count data. The Multivariate Autoregressive Conditional Poisson model (MACP) makes it possible to deal withissues of discreteness, overdispersion (variance greater thant then mean) and both auto- and crosscorrelation. We model counts...

The number of Norwegian guest nights in Swedish hotels and cottages is studied. Aggregation of an integer-valued AR(1) model and a two-stage demand model underlies the empirical results. The parameters in the model are check-out probability, mean check-in and the probability of selecting the...