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The purpose of this paper is to examine the causal relationships between inflation, output growth and their uncertainties in Malaysia.

The modeling approach allows for structural breaks to avoid the masking of specific impacts.

Based on the asymmetric Generalized Autoregressive Conditional Heteroskedasticity model, the paper found strong evidence favoring a positive effect of a change in the inflation uncertainty as predicted by the Friedman-Ball hypothesis. In addition, inflation (inflation uncertainty) has direct (indirect) negative effect on the output growth. The results are consistent with the Taylor effect – increases in inflation uncertainty decreases output uncertainty. The analysis also reveals that economic uncertainty lowers the growth rate of output, complying with Bernanke's idea.

The present study suggests that extra efforts are required to locate the breaks in the variance in order to draw concrete evidence on link between economic uncertainty and macroeconomic performance.

The purpose of this paper is to determine the relationship between inflation, inflation uncertainty, growth and growth uncertainty for Australia.

Multivariate EGARCH models has been used to estimate the relationship between inflation, inflation uncertainty, growth and growth uncertainty for Australia.

Using quarterly data in multivariate EGARCH models, this study finds that both inflation uncertainty and output uncertainty have negative and significant effects on output growth. The paper also finds that, while inflation uncertainty has a positive and significant effect on inflation, output uncertainty has a negative and significant effect on inflation. The study uses a newly constructed oil price dummy as a control variable and finds that oil price changes significantly increase inflation uncertainty. The study also finds that inflation uncertainty and the inflation level have both declined since the adoption of a formal inflation‐targeting monetary policy in Australia.

Multivariate EGARCH model can be used to estimate the effects of inflation, inflation uncertainty, growth and growth uncertainty for cross‐country analysis.

This is the first study of the effect of inflation uncertainty and growth uncertainty on inflation and growth in Australia using a newly constructed oil price dummy in a multivariate EGARCH framework.

Prior research has emphasised the importance of the early phases of construction projects, as well as the difficulties of procuring engineering services – especially due to the uncertainties. Despite that, studies on the public procurement of engineering services are scarce. Although scholars have shown that uncertainty may affect the choice of control modes, the level of uncertainty that characterises services is not addressed by the two task characteristics: knowledge of the transformation process and output measurability. The purpose is to investigate organisational control in public procurement of engineering services.

The existing control model was adjusted in this study by conceptually adding uncertainty as a third aspect to the two task characteristics. A single case study of the Swedish Transport Administration was used. The empirical data, comprising 14 interviews with managers from the client and engineering consulting companies, were analysed using flexible pattern matching and visual mapping approaches and then illustrated using the model.

The public client did not base its choice of control modes on uncertainty, but rather on the other two task characteristics. Consequently, the service providers argued that the chosen control modes reduced their creativity, increased their financial risks and caused unclear responsibilities. This study therefore shows that uncertainty is an important factor to consider in the choice of control modes, both from a theoretical perspective and from the service providers' point of view. The developed model may therefore be useful for researchers as well as practitioners.

This study is the first attempt to add uncertainty as a task characteristic when choosing control modes. The results contribute to the scarce control literature regarding the procurement of engineering services for construction projects and the procurement of other services with high uncertainty.

The study examines the effect of increased Economic Policy uncertainty on analyst optimism in the Indian market. The study also explores whether the SEBI Research Analyst Regulation, 2014, has effectively contained the optimistic nature of analysts.

The study is based on firms in the Indian market. The sample period is 2003–2020. It runs a linear panel regression to measure the impact of Economic Policy uncertainty on the optimism level of analysts' forecasts and recommendations, controlling for firm fixed effects. Further, the impact of the SEBI Research Analyst Regulation, 2014, has been assessed with the help of the difference-in-difference approach.

The Economic Policy uncertainty is significantly and positively related to the analyst optimism, reflected in the forecast bias and recommendation in the Indian context. The experience of analysts and the age of the firm positively drive optimism. However, introducing the Research Analyst Regulation by SEBI led to a decline in analyst optimism. The regulation decoupled the analysts' compensation from brokerage service transactions. Thus, the results suggest that the regulation has effectively curbed the incentive to produce optimistic output.

This is the first study in the Indian market to assess the impact of uncertainty on analyst output. It also investigates the effectiveness of the first analyst-specific regulation in India, i.e. The Research Analyst Regulation, 2014.

This empirical study examines the impact of context‐team factors and team‐employee factors on perceived uncertainty in self‐managed service teams. The results of our study show that context‐team factors rather than team‐employee factors are critical to the extent of uncertainty employees perceive when providing customer service. Furthermore, perceived uncertainty has negative impact on self‐managed team outcomes in terms of job satisfaction and intention to leave the team. Besides this, our findings indicate that team commitment to customer service quality can serve as an effective tool to handle the negative consequences of perceived uncertainty in self‐managed service teams. Finally, in addition to the cross‐sectional analysis, a longitudinal exploration has been carried out, the outcomes of which suggest that the structural relationships are changing over time, underlining the need to take dynamic considerations into account in analyzing the effectiveness of self‐managed work teams.

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.

The purpose of this paper is to present a realistic hedging model.

The paper uses a general utility function, general distributions, and a multiple‐input technology.

The study finds that the impact of one or both risks on the optimal output, hedge, or hedge ratio is determined by the market structure of one or both forward pieces.

This is the first paper that uses a general, complete, and realistic hedging model.

This study investigated the asymmetric effects of changes in policy uncertainty on real sector variables in Brazil, China, India and South Africa.

The study used the nonlinear autoregressive distributed lag (NARDL) modeling framework.

The results showed that both in the long run and short run, rising uncertainty not only increases consumer prices significantly in these economies, but also impedes aggregate and sectoral output growths, and deters investment, employment and private consumption. Contrary to economic expectation, the results also showed that in the long run, declining uncertainty impedes aggregate and sectoral output growths in these economies, and significantly hinders employment in South Africa and Brazil. This suggests that in the long run, economic agents in these economies somewhat behave as if uncertainty is rising. The authors also found significant asymmetric effects in the response of real sector variables to uncertainty both in the long run and short run, which justifies the choice of NARDL framework for this study.

The sample is limited to Brazil, India, China and South Africa. While Brazil, India and China are three of the most prominent large emerging market economies, South Africa is the largest emerging market economy in Africa.

To lessen the adverse effects of policy uncertainty observed in the results, there is need for sound institutions and policy regimes that can promote predictable policy responses in these economies so that policy neither serves as a source of uncertainty nor as a channel through which the effects of other shocks are transmitted.

Apart from using the NARDL framework to capture the asymmetric effects of policy uncertainty, this study also accounted for the sectoral effects of uncertainty in emerging markets.

The purpose of this paper is to study the evolution of monetary policy uncertainty and its impact on the South African economy.

The authors use a sign restricted SVAR with an endogenous feedback of stochastic volatility to evaluate the sign and size of uncertainty shocks. The authors use a nonlinear DSGE model to gain deeper insights about the transmission mechanism of monetary policy uncertainty.

The authors show that monetary policy volatility is high and constant. Both inflation and interest rates decline in response to uncertainty. Output rebounds quickly after a contemporaneous decrease. The DSGE model shows that the size of the uncertainty shock matters – high uncertainty can lead to a severe contraction in output, inflation and interest rates.

The authors model only a few variables in the SVAR – thus missing perhaps other possible channels of shock transmission.

There is a lesson for monetary policy: monetary policy uncertainty, in isolation from general macroeconomic uncertainty, often creates unintended adverse consequences and can perpetuate a weak economic environment. The tasks of central bankers are incredibly difficult. Their models project output and inflation with relatively large uncertainty based on many shocks emanating from various sources. It matters how central bankers react to these expectations and how they communicate the underlying risks associated with setting interest rates.

This is the first study that looks into monetary policy uncertainty into South Africa using a stochastic volatility model and a nonlinear DSGE model. The results should be very useful for the Central Bank as it highlights how uncertainty, that they create, can have adverse economic consequences.

This article examines the behaviour of a labour‐managed firm operating in a world in which the output price is uncertain, but it varies betwen a price floor and a price ceiling. We show that risk aversion is sufficient to give the direct relationship between a change in uncertainty and the optimal level of output for the labour‐managed firm, which is weaker than the decreasing absolute risk aversion assumption imposed by Hawawini and Michel (1979), Hey and Suckling (1980), Hey (1981a) and Paroush and Kahana (1980).