We propose a family of CUSUM-based statistics to detect the presence changepoints in deterministic part autoregressive parameter Random Coefficient Autoregressive (RCA) sequence. Our tests can be applied irrespective whether sequence is stationary or not, and no prior knowledge stationarity lack thereof required. Similarly, our even when error term stochastic coefficient are non iid, covering c...

This paper provides numerically trivial estimators for short panels of either binary choices or of linear models that suffer from confounded, missing not at random sample selection. The estimators allow for Þxed effects, endogenous regressors, weakly exogenous regressors, and heterokedastic errors with unknown distribution. The estimators, which converge at rate root n, are based on variants of...

The coefficient of determination (R) is used for judging the goodness of fit in a linear regression model. It gives valid results only when the observations are correctly observed without any measurement error. The R provides invalid results in the presence of measurement errors in the data in the sense that sample R becomes an inconsistent estimator of population multiple correlation coefficie...

We review the basic principles for the evaluation of design efficiency in discrete choice modelling with a focus on efficiency of WTP estimates from the multinomial logit model. The discussion is developed under the realistic assumption that researchers can plausibly define a prior on the utility coefficients. Some new measures of design performance in applied studies are proposed and their rat...

Agricultural production systems face increasing threats from more frequent and extreme weather fluctuations associated with global climate change. While there is mounting evidence that increased plant community diversity can reduce the variability of ecosystem functions (such as primary productivity) in the face of environmental fluctuation, there has been little work testing whether this is tr...

Consideration set models relax the assumption that consumers are aware of all available options. Thus far, identification arguments for these models have relied either on auxiliary data on what options were considered or on instruments excluded from consideration or utility. In a discrete choice framework subsuming logit, probit and random coefficients models, we prove that utility and consider...