25 resultados para uncertainty estimation

em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom


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While estimates of models with spatial interaction are very sensitive to the choice of spatial weights, considerable uncertainty surrounds de nition of spatial weights in most studies with cross-section dependence. We show that, in the spatial error model the spatial weights matrix is only partially identi ed, and is fully identifi ed under the structural constraint of symmetry. For the spatial error model, we propose a new methodology for estimation of spatial weights under the assumption of symmetric spatial weights, with extensions to other important spatial models. The methodology is applied to regional housing markets in the UK, providing an estimated spatial weights matrix that generates several new hypotheses about the economic and socio-cultural drivers of spatial di¤usion in housing demand.

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This paper develop and estimates a model of demand estimation for environmental public goods which allows for consumers to learn about their preferences through consumption experiences. We develop a theoretical model of Bayesian updating, perform comparative statics over the model, and show how the theoretical model can be consistently incorporated into a reduced form econometric model. We then estimate the model using data collected for two environmental goods. We find that the predictions of the theoretical exercise that additional experience makes consumers more certain over their preferences in both mean and variance are supported in each case.

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We analyse the role of time-variation in coefficients and other sources of uncertainty in exchange rate forecasting regressions. Our techniques incorporate the notion that the relevant set of predictors and their corresponding weights, change over time. We find that predictive models which allow for sudden rather than smooth, changes in coefficients significantly beat the random walk benchmark in out-of-sample forecasting exercise. Using innovative variance decomposition scheme, we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients' variability, as the main factors hindering models' forecasting performance. The uncertainty regarding the choice of the predictor is small.

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This paper does two things. First, it presents alternative approaches to the standard methods of estimating productive efficiency using a production function. It favours a parametric approach (viz. the stochastic production frontier approach) over a nonparametric approach (e.g. data envelopment analysis); and, further, one that provides a statistical explanation of efficiency, as well as an estimate of its magnitude. Second, it illustrates the favoured approach (i.e. the ‘single stage procedure’) with estimates of two models of explained inefficiency, using data from the Thai manufacturing sector, after the crisis of 1997. Technical efficiency is modelled as being dependent on capital investment in three major areas (viz. land, machinery and office appliances) where land is intended to proxy the effects of unproductive, speculative capital investment; and both machinery and office appliances are intended to proxy the effects of productive, non-speculative capital investment. The estimates from these models cast new light on the five-year long, post-1997 crisis period in Thailand, suggesting a structural shift from relatively labour intensive to relatively capital intensive production in manufactures from 1998 to 2002.

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Recent attempts to incorporate optimal fiscal policy into New Keynesian models subject to nominal inertia, have tended to assume that policy makers are benevolent and have access to a commitment technology. A separate literature, on the New Political Economy, has focused on real economies where there is strategic use of policy instruments in a world of political conflict. In this paper we combine these literatures and assume that policy is set in a New Keynesian economy by one of two policy makers facing electoral uncertainty (in terms of infrequent elections and an endogenous voting mechanism). The policy makers generally share the social welfare function, but differ in their preferences over fiscal expenditure (in its size and/or composition). Given the environment, policy shall be realistically constrained to be time-consistent. In a sticky-price economy, such heterogeneity gives rise to the possibility of one policy maker utilising (nominal) debt strategically to tie the hands of the other party, and influence the outcome of any future elections. This can give rise to a deficit bias, implying a sub-optimally high level of steady-state debt, and can also imply a sub-optimal response to shocks. The steady-state distortions and inflation bias this generates, combined with the volatility induced by the electoral cycle in a sticky-price environment, can significantly

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The paper studies the interaction between cyclical uncertainty and investment in a stochastic real option framework where demand shifts stochastically between three different states, each with different rates of drift and volatility. In our setting the shifts are governed by a three-state Markov switching model with constant transition probabilities. The magnitude of the link between cyclical uncertainty and investment is quantified using simulations of the model. The chief implication of the model is that recessions and financial turmoil are important catalysts for waiting. In other words, our model shows that macroeconomic risk acts as an important deterrent to investments.

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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.

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While flexible exchange rates facilitate stabilisation, exchange rate fluctuations can cause real volatility. This gives policy importance to the causal relationship between exchange rate depreciation and its volatility. An exchange rate may be expected to become more volatile when the underlying currency loses value. We conjecture that a reverse causation, which further weakens the currency, may be mitigated by price stability. Data from Ghana, Mozambique and Tanzania support this: depreciation makes exchange rate more volatile for all but volatility does not causes depreciation in Tanzania which has enjoyed a more stable inflation despite all countries adopting similar macro-policies since early 1990s.

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This paper uses a micro-founded DSGE model to compare second-best optimal environmental policy and the resulting allocation to first-best allocation. The focus is on the source and size of uncertainty, and how this affects optimal choices and the inferiority of second best vis-à-vis first best.

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This paper examines the impact of Knightian uncertainty upon optimal climate policy through the prism of a continuous-time real option modelling framework. We analytically determine optimal intertemporal climate policies under ambiguous assessments of climate damages. Additionally, numerical simulations are provided to illustrate the properties of the model. The results indicate that increasing Knightian uncertainty accelerates climate policy, i.e. policy makers become more reluctant to postpone the timing of climate policies into the future.

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We construct a model in which oligopolistic firms decide between locating in a country where employment protection implies costly output adjustments and in one without employment protection. Using a two-period three-stage game with uncertainty, we demonstrate that location is influenced by both flexibility and strategic concerns. The strategic effects under Cournot work towards domestic anchorage in the country with employment protection while those under Bertrand do not. Strategic agglomeration can occur in the inflexible country under Cournot and even under Bertrand, provided uncertainty and foreign direct investment costs are low.

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This paper models the decision to quit smoking like an investment decision where the quitter incurs a sunk withdrawal cost today and forgoes their consumer surplus from cigarettes (invests) and hopes to reap an uncertain reward of better health and therefore higher utility in the future (return). We show that a risk-averse mature smoker who expects to benefit from quitting may still rationally choose to delay quitting until they are more confident that quitting is the right decision for them. Such a decision by the smoker is due to the value associated with keeping their option of whether or not to quit open as they learn more about the damage that smoking will have on their future utility. Policies which reduce a smoker’s uncertainty about the damage that smoking with have on their future utility is likely to make them quit earlier.

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This paper is a contribution to the growing literature on constrained inefficiencies in economies with financial frictions. The purpose is to present two simple examples, inspired by the stochastic models in Gersbach-Rochet (2012) and Lorenzoni (2008), of deterministic environments in which such inefficiencies arise through credit constraints. Common to both examples is a pecuniary externality, which operates through an asset price. In the second example, a simple transfer between two groups of agents can bring about a Pareto improvement. In a first best economy, there are no pecuniary externalities because marginal productivities are equalised. But when agents face credit constraints, there is a wedge between their marginal productivities and those of the non-credit-constrained agents. The wedge is the source of the pecuniary externality: economies with these kinds of imperfections in credit markets are not second-best efficient. This is akin to the constrained inefficiency of an economy with incomplete markets, as in Geanakoplos and Polemarchakis (1986).

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We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.