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Strong versions of the Precautionary Principle (PP) require regulators to prohibit or impose technology controls on activities that pose uncertain risks of possibly significant environmental harm. This decision rule is conceptually unsound and would diminish social welfare. Uncertainty as such does not justify regulatory precaution. While they should reject PP, regulators should take appropriate account of societal aversion to risks of large harm and the value of obtaining additional information before allowing environmentally risky activities to proceed.

The purpose of this paper is to empirically analyze the impact of macroeconomic uncertainty on a large sample of 19 commodity markets.

The authors rely on Jurado et al.’s (2015) measure of macroeconomic uncertainty based on a wide range of monthly macroeconomic and financial indicators and estimate a threshold VAR model to assess whether the impact of macroeconomic uncertainty on commodity prices differs under the high- or low-uncertainty state.

The findings show that positive macroeconomic uncertainty shocks affect commodity prices returns negatively on average and the impact of macroeconomic uncertainty is generally higher in high-uncertainty states compared with low-uncertainty states. Besides, although the safe-haven role of precious metals is confirmed, energy and industrial markets are more sensitive to short-run and long-run macroeconomic uncertainty, respectively.

The findings in this study suggest that commodity prices reflect not only the level of economic fundamental but also the volatility of economic fundamental.

This study empirically analyzes and verifies the influence of macroeconomic uncertainty not only on oil prices but also on four groups of 19 raw materials. As for the methodological issues, the authors rely on a structural threshold vector autoregressive specification for modeling commodity price returns to account for potentially different effects depending on the macroeconomic uncertainty states.

This paper deals with estimation of risk and the risk preference function when producers face uncertainties in production (usually labeled as production risk) and output price. These uncertainties are modeled in the context of production theory where the objective of the producers is to maximize expected utility of normalized anticipated profit. Models are proposed to estimate risk preference of individual producers under (i) only production risk, (ii) only price risk, (iii) both production and price risks, (iv) production risk with technical inefficiency, (v) price risk with technical inefficiency, and (vi) both production and price risks with technical inefficiency. We discuss estimation of the production function, the output risk function, and the risk preference functions in some of these cases. Norwegian salmon farming data is used for an empirical application of some of the proposed models. We find that salmon farmers are, in general, risk averse. Labor is found to be risk decreasing while capital and feed are found to be risk increasing.

This study aims to examine short- and long-run effects of specific macroeconomic conditions on risk premium estimates on lending.

Empirical estimates are based on error correction and autoregressive distributed lag models.

The results suggest that, in the short run, inflation expectations, recession expectations and actual inflationary conditions tend to have a significant impact on risk premium estimates; in the long run, however, only inflation expectations and recession expectations are significant in risk premium estimates on lending.

This study examines how specific conditions of uncertainty and expectations influence variability in risk premium estimates on lending in the US economy.

The purpose of this paper is to estimate the effect of policy and exchange rate uncertainty shocks on EU countries’ exports to the world economy. The authors examine the performance of the four biggest economies, namely Germany, France, Italy and the UK, under policy and exchange rate uncertainty in exports to some of the most important global export destinations (the USA, Japan, Brazil, Russia and China).

For this purpose, the authors apply a non-linear model, where suddenly strong spurts of exports occur when changes of the exchange rate go beyond a zone of inaction, which the authors call “play” area – analogous to mechanical play. The authors implement an algorithm describing path-dependent play hysteresis into a regression framework. The hysteretic impact of real exchange rates on exports is estimated based on the period from 1995M1 to 2015M12.

Looking at some of the main export destinations of the selected EU member countries, the USA, Japan and some of the members of BRICS (Brazil, Russia and China), the authors identify significant hysteretic effects for a large part of the EU member countries’ exports. The authors find that their export activity is characterized by “bands of inaction” with respect to changes in the real exchange. To check for robustness, the authors estimate export equations for limited samples: excluding the recent financial crisis and excluding the period up to the burst of the dotcom bubble and September 11. In addition, the authors employ an economic policy uncertainty variable and an exchange rate uncertainty variable as determinants of the width of the area of weak reaction of exports.

Overall, the authors find that those specifications which take uncertainty into account display the highest goodness of fit, with economic policy uncertainty dominating exchange rate uncertainty. In other words, the option value of waiting dominates the real exchange rate effect on the EU member countries’ exports.

The existence of “bands of inaction” (called “play”) in EU member countries’ exports should lead to a more objective discussion of peaks and troughs in those countries’ real exchange rates and, more specifically, of the relevance of internal and external devaluation and other indicators to gain international competitiveness on exports in political debates. If policy and/or exchange rate uncertainty are diminished, one may expect an earlier boost in exports, if the home currency is devaluing in real terms.

The results are useful as arguments in the debate about exchange rate pain threshold vs export triggers.

The authors focus on the export performance of the four biggest economies in the European Union, namely Germany, France, Italy and the UK. The authors examine their respective export performance, as an innovation, under policy and exchange rate uncertainty and, for this purpose, look at some of the most important global export destinations (the USA, Japan and the BRICS (Brazil, Russia and China)). The authors do so, also as an innovation, by differentiating between intervals of weak and strong reaction of their exports to real exchange rate changes.

The purpose of this paper is twofold: first, to suggest a modified sales comparison model that is scalable and adaptable to value under conditions of certainty and uncertainty. The model can potentially be applied to residential property, non-residential property and large item plant and machinery in determining the value, rental or capitalisation rate. The second purpose is to address practitioner and end user bias, which if unaddressed can lead to potentially inconsistent valuation results.

Literature was reviewed on decision theory, specifically cognitive limitations, heuristics and biases. A qualitative approach is followed in the paper although the output of the proposed model itself is quantitative.

The paper argues that practitioners and end users alike tend to avoid advanced statistical techniques when valuing under conditions of certainty, while advanced statistical techniques would not be possible under conditions of uncertainty. In addition, practitioners can, due to the representative heuristic, be over-confident in their ability, skill or knowledge when performing valuations under conditions of certainty. When valuing under conditions of uncertainty, practitioners tend to avoid simple rule models as they consider the process too unique to be standardised. The combined effect is inconsistent valuation results unless it can potentially be addressed through an integrated and modified sales comparison model that takes into account varying degrees of certainty and uncertainty.

The proposed modified sales comparison model is an integrated model that can be adopted by practitioners in valuing residential, non-residential and large plant and machinery. It can potentially be used to value under conditions of certainty and uncertainty and improve valuation consistency. End users such as mortgage lenders and investors can benefit from the adoption of this model.

The aim of this paper is to propose an integrated and modified sales comparison model for valuing under conditions of certainty, normal uncertainty and abnormal uncertainty. The integrated model can value based on direct comparison under conditions of certainty and uncertainty while addressing the in practice avoidance of advanced statistical techniques and the implications of the representative heuristic and halo effect as cognitive biases on valuation consistency.

The objective of this paper is threefold. First, it aims to empirically study whether firm-specific/idiosyncratic uncertainty, macroeconomic/aggregate uncertainty and political uncertainty have an adverse influence on firms' investment decisions in Pakistan. After establishing this, it scrutinizes whether the uncertainty effects on investment are different for firms of different sizes. Finally, it investigates whether any heterogeneity exists in the uncertainty impacts across different industries.

The empirical analysis is based on an unbalanced panel data of 468 nonfinancial firms listed at the Pakistan Stock Exchange (PSX) during the period 2000–2018. Departing from the literature, the paper builds a time-varying composite volatility/uncertainty index based on the principal component analysis (PCA) by utilizing the constructed volatility series for sales, cash flows and return on assets to gauge firm-specific uncertainty for each firm included in the analysis. Likewise, the paper develops a PCA-based composite index for macroeconomic uncertainty by using the conditional variance series of consumer price index (CPI), industrial production index (IPI), the interest rate and the exchange rate obtained by estimating the (generalized) autoregressive conditional heteroscedastic, (G)ARCH, models. Finally, political uncertainty is measured by political risk components maintained by the Political Risk Services Group. The empirical framework of the paper augments the standard investment equation by incorporating all three types of uncertainty. Firms are grouped into small, medium and large categories based on firms' total assets and the size indicators are generated. Next, the indicators are multiplied by each uncertainty measure to quantify the differential effects of uncertainty across firm size. Firms are also differentiated by sectors to explore the sector-based asymmetries in the uncertainty effects. The “robust two-step system generalized method of moments (2SYS GMM) (dynamic panel data) estimator” is applied to estimate the empirical models.

The results provide robust and strong evidence of the detrimental influence of all three types of uncertainty on investment. Yet, it is observed that the strength of the influence considerably varies across uncertainty types. In particular, compared to firm-specific uncertainty, both macroeconomic and political uncertainties have more unfavorable effects. The analysis also reveals that the effects of all three types of uncertainty are quite different at small, medium and large firms. Specifically, it is observed that although the investment of all firms is influenced adversely by magnified uncertainty, the adverse effects of all three kinds of uncertainty are quite stronger at small firms than medium and large firms. These findings support the phenomenon of size-based asymmetries in the effects of uncertainty on investment. The results also provide evidence that either type of uncertainty quite differently affects the investment policy of firms in different sectors.

The findings help different stakeholders to know how different types of uncertainty differently affect corporate firms' investments. Further, they suggest that firm size has a vital role in ascertaining the adverse effects of uncertainty on investment. The paper identifies to which type of uncertainty investors and policymakers should care more about and to which types of firms and industries they should concern more during volatile times. Firms should have more fixed assets and expand their size to mitigate the detrimental effects on investment of internal and external uncertainties. The government should enhance the political stability to induce firms for a higher level of investment, which, in turn, will result in higher growth of the economy.

The originality of the paper is credited to four aspects. First, unlike most previous studies that have utilized a single volatility measure, this paper constructs composite uncertainty indices based on the weights determined by the PCA. Second, it examines the effect of political uncertainty over and above the effects of idiosyncratic and aggregate (macroeconomic uncertainty) for an emerging economy. Third, and most important, it provides first-hand empirical evidence on the role of firm size in establishing the asymmetric effects of uncertainty on investment. Finally, it provides evidence on the industry-based heterogeneity in the uncertainty effects.