The Effect of Exchange Rate Uncertainty on US Imports from the UK: Consistent OLS Estimation with Volatility Measured by An ARCH-type Model

This paper investigates the effect of exchange rate volatility on US-UK bilateral trade flows. As part of econometric problems arising from a generated variable, we consider a special case when an ARCH type auxiliary model is used to measure uncertainty in the exchange rate and discuss a procedure for the correct inference of the OLS estimates of the primary equation in the second stage, which includes the generated variable. By applying this two-step approach, we find a statistically significant, negative impact of exchange rate uncertainty on US imports from the United KinARCH model; Consistent estimation; Generated regressors; Volatility

The effect of exchange rate uncertainty on US imports from the UK: Consistent OLS estimation with volatility measured by an ARCH-type model

This paper investigates the effect of exchange rate volatility on US-UK bilateral trade flows. As part of econometric problems arising from a generated variable, we consider a special case when an ARCH type auxiliary model is used to measure uncertainty in the exchange rate and discuss a procedure for the correct inference of the OLS estimates of the primary equation in the second stage, which includes the generated variable. By applying this two-step approach, we find a statistically significant, negative impact of exchange rate uncertainty on US imports from the United KingdomARCH model; Consistent OLS estimation; Generated regressors;

Model Identification and Non-unique Structure

Identification is an essential attribute of any model's parameters, so we consider its three aspects of 'uniqueness', 'correspondence to reality' and 'interpretability'. Observationally-equivalent over-identified models can co-exist, and are mutually encompassing in the population; correctly-identified models need not correspond to the underlying structure; and may be wrongly interpreted. That a given model is over-identified with all over-identifying restrictions valid (even asymptotically) is insufficient to demonstrate that it is a unique representation. Moreover, structre (as invariance under extended information) need not be identifiable. We consider the role of structural breaks to discriminate between such representations.

Specification Test for Fixed Effects in Binary Panel Data Model: A Simulation Study

Abstract In this paper, we examine the specification tests which have been proposed for fixed effects in binary panel data model, using several different data generating processes to evaluate the performance of the specification test in different situations. By simulations, we find the specification test based on moment conditions is able to outperform the Lagrange multiplier test proposed b

The encompassing principle and evaluation of econometric models

Encompassing, as a general principle of econometric model building and evaluation, has been suggested by, e.g., Hendry and Richard (1982), Mizon and Richard (1986). The recent development of encompassing can be found in Hendry and Richard (1990). The purpose of this research is to further investigate the structure and properties of encompassing, its relationship with other testing framework, e.g. m-testing framework, and its application in evaluating simultaneous equation systems. In this thesis, it has been shown that encompassing as a general testing principle is, under some regularity conditions, equivalent to the conditional moment testing framework (m-testing) suggested by Newey (1985) and Tauchen (1985). It also has been shown that the equivalence of two econometric models in the sense of encompassing has the same connotation as that established under the Kullback criterion (Kullback (1959)). The applications of encompassing to evaluating non-nested models that are part of simultaneous equations systems can be found in Chapter 5. The forecasting encompassing is discussed in Chapter 6. </p

Mutual encompassing and model equivalence

This paper analyzes the properties of mutual encompassing and its relationship to the KLIC equivalence between statistical models. It is shown that models are KLIC equivalent if and only if they are mutually encompassing and mutually Cox encompassing. Further, within the exponentional family encompassing implies Cox-encompassing and so mutual encompassing is necessary and sufficient for KLIC equivalence in this family. In addition, it is shown that mutual encompassing is transitive for models in the exponential family

Model identification and non-unique structure

Identification is an essential attribute of any model’s parameters, so we consider its three aspects of ‘uniqueness’, ‘correspondence to reality’ and ‘interpretability’. Observationally-equivalent overidentified models can co-exist, and are mutually encompassing in the population; correctly-identified models need not correspond to the underlying structure; and may be wrongly interpreted. That a given model is over-identified with all over-identifying restrictions valid (even asymptotically) is insufficient to demonstrate that it is a unique representation. Moreover, structure (as invariance under extended information) need not be identifiable. We consider the role of structural breaks to discriminate between such representations

The Robustness of Trend Stationarity: An Illustration with the Extended Nelson-Plosser Dataset

We re-evaluate Andreu and Spanos's findings in favour of trend stationarity by considering the extended Nelson-Plosser data set. This expanded (to 1988) data set includes a period of rather different behaviour compared with the original Nelson-Plosser data used by Andreou and Spanos. We find that Andreou and Spanos's models (with only minor adjustments) exhibit remarable stability over this extended period, and indicate that their conclusions are more robust than they have shown.Difference stationarity, Trend stationarity, Unit root test,

The robustness of trend stationarity: an illustration with the extended Nelson-Plosser dataset

We re-evaluate Andreu and Spanos's findings in favour of trend stationarity by considering the extended Nelson–Plosser data set. This expanded (to 1988) data set includes a period of rather different behaviour compared with the original Nelson–Plosser data used by Andreou and Spanos. We find that Andreou and Spanos's models (with only minor adjustments) exhibit remarable stability over this extended period, and indicate that their conclusions are more robust than they have shown

The encompassing principle and specification tests

Digitised version produced by the EUI Library and made available online in 2020