Growth Rate Estimation in the presence of Unit Roots

This study addresses the issue of the presence of a unit root on the growth rate estimation by the least-squares approach. We argue that when the log of a variable contains a unit root, i.e., it is not stationary then the growth rate estimate from the log-linear trend model is not a valid representation of the actual growth of the series. In fact, under such a situation, we show that the growth of the series is the cumulative impact of a stochastic process. As such the growth estimate from such a model is just a spurious representation of the actual growth of the series, which we refer to as a “pseudo growth rate”. Hence such an estimate should be interpreted with caution. On the other hand, we highlight that the statistical representation of a series as containing a unit root is not easy to separate from an alternative description which represents the series as fundamentally deterministic (no unit root) but containing a structural break. In search of a way around this, our study presents a survey of both the theoretical and empirical literature on unit root tests that takes into account possible structural breaks. We show that when a series is trendstationary with breaks, it is possible to use the log-linear trend model to obtain well defined estimates of growth rates for sub-periods which are valid representations of the actual growth of the series. Finally, to highlight the above issues, we carry out an empirical application whereby we estimate meaningful growth rates of real wages per worker for 51 industries from the organised manufacturing sector in India for the period 1973-2003, which are not only unbiased but also asymptotically efficient. We use these growth rate estimates to highlight the evolving inter-industry wage structure in India.

The Impacts of Temporary and Anticipated Tourism Spending.

Part of the local economic impact of a major sporting event comes from the associated temporary tourism expenditures. Typically demand-driven Input-Output (IO) methods are used to quantify the impacts of such expenditures. However, IO modelling has specific weaknesses when measuring temporary tourism impacts; particular problems lie in its treatment of factor supplies and its lack of dynamics. Recent work argues that Computable General Equilibrium (CGE) analysis is more appropriate and this has been widely applied. Neglected in this literature however is an understanding of the role that behavioural characteristics and factor supply assumptions play in determining the economic impact of tourist expenditures, particularly where expenditures are temporary (i.e. of limited duration) and anticipated (i.e. known in advance). This paper uses a CGE model for Scotland in which agents can have myopic- or forward-looking behaviours and shows how these alternative specifications affect the timing and scale of the economic impacts from anticipated and temporary tourism expenditure. The tourism shock analysed is of a scale expected for the Commonwealth Games to be held in Glasgow in 2014. The model shows how “pre-shock” and “legacy” effects – impacts before and after the shock – arise and their quantitative importance. Using the forward-looking model the paper calculates the optimal degree of pre-announcement.