Real exchange rate fluctuations, endogenous tradability and exchange rate regimes

The real exchange rate is driven by fluctuations of the relative price of traded goods and the relative price of nontraded to traded goods. This study explains the variance decomposition of the real exchange rate using a stochastic dynamic general equilibrium model of comparative advantage with money. Given interest rate shocks, exchange rate stability reduces the covariance between the two relative prices and raises the contribution of the relative price of nontraded to traded goods. Productivity shocks do not alter the covariance across exchange rate regimes and let the relative price of traded goods drive the real exchange rate.     

From circular business models to circular business ecosystems

The circular economy aims to minimize resource inputs and waste and emission outputs of the economy and its organizational subsystems. This can benefit both financial and sustainability performance of companies. To analyze industrial implementation of the concept, the prevalent unit of analysis on the firm level is currently the circular business model. Our investigation of nine Swedish biogas companies and one branch organization indicates a range of conceptual shortcomings that challenges this approach. Our comparative case analysis points towards circular ecosystems being a more appropriate concept to describe the high level of coordination between different stakeholders necessary to implement circular systems. This increases the suitability to analyze, plan, and communicate circular economy systems on an organizational level, especially if value chain integration is low. An ecosystem perspective can thus support innovation and entrepreneurship in the context of the circular economy.     

Mixed Oligopoly at Free Entry Markets

We investigate the optimal behavior of a public firm in a mixed market involving private firms and one public firm. Existing works show that welfare-maximizing behavior by the public firm is suboptimal when the number of firms is given exogenously. We allow free entry of private firms and find that, in contrast to the case with the fixed number of firms, welfare-maximizing behavior by the public firm is always optimal in mixed markets. Furthermore, we find that mixed markets are better than pure markets involving no public firm if and only if the public firm earns nonnegative profits.     

Real exchange rate fluctuations,wage stickiness and tradability

When we classify factors of production by their tradability, the relative wage of nontraded labour influences the real exchange rate through the relative cost of distribution services. We confirm this prediction using monthly data on the sector‐level US–Canada real exchange rate and the relative wage of service‐producing labour. The relative wage accounts for 40% of the variability of the real exchange rate at a one‐month horizon. Furthermore, when we use the effective nontraded labour content to classify goods into nontraded and traded ones, the variability of the price of the nontraded‐goods basket accounts for more than half of the variability of the real exchange rate.     

Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings*

In this paper we analyze whether presidential approval ratings can predict the S&P 500 returns over the monthly period of July 1941 to April 2018, using a dynamic conditional correlation multivariate generalized autoregressive conditional heteroscedasticity (DCC‐MGARCH) model. Our results show that standard linear Granger causality test fail to detect any evidence of predictability. However, the linear model is found to be misspecified due to structural breaks and nonlinearity, and hence, the result of no causality from presidential approval ratings to stock returns cannot be considered reliable. When we use the DCC‐MGARCH model, which is robust to such misspecifications, in 69% of the sample period, approval ratings in fact do strongly predict the S&P 500 stock return. Moreover, using the DCC‐MGARCH model we find that presidential approval rating is also a strong predictor of the realized volatility of S&P 500. Overall, our results highlight that presidential approval ratings is helpful in predicting stock return and volatility, when one accounts for nonlinearity and regime changes through a robust time‐varying model.     

DSGE model-based forecasting of modelled and nonmodelled inflation variables in South Africa

Inflation forecasts are a key ingredient for monetary policy-making – especially in an inflation targeting country such as South Africa. Generally, a typical Dynamic Stochastic General Equilibrium (DSGE) only includes a core set of variables. As such, other variables, for example alternative measures of inflation that might be of interest to policy-makers, do not feature in the model. Given this, we implement a closed-economy New Keynesian DSGE model-based procedure which includes variables that do not explicitly appear in the model. We estimate such a model using an in-sample covering 1971Q2 to 1999Q4 and generate recursive forecasts over 2000Q1 to 2011Q4. The hybrid DSGE performs extremely well in forecasting inflation variables (both core and nonmodelled) in comparison with forecasts reported by other models such as AR(1). In addition, based on ex-ante forecasts over the period 2012Q1–2013Q4, we find that the DSGE model performs better than the AR(1) counterpart in forecasting actual GDP deflator inflation.     

Forecasting South African inflation using non-linearmodels: a weighted loss-based evaluation

The conduct of inflation targeting is heavily dependent on accurate inflation forecasts. Non-linear models have increasingly featured, along with linear counterparts, in the forecasting literature. In this study, we focus on forecasting South African inflation by means of non-linear models and using a long historical dataset of seasonally adjusted monthly inflation rates spanning from 1921:02 to 2013:01. For an emerging market economy such as South Africa, non-linearities can be a salient feature of such long data, hence the relevance of evaluating non-linear models’ forecast performance. In the same vein, given the fact that 1969:10 marks the beginning of a protracted rising trend in South African inflation data, we estimate the models for an in-sample period of 1921:02–1966:09 and evaluate 1, 4, 12, and 24 step-ahead forecasts over an out-of-sample period of 1966:10–2013:01. In addition, using a weighted loss function specification, we evaluate the forecast performance of different non-linear models across various extreme economic environments and forecast horizons. In general, we find that no competing model consistently and significantly beats the LoLiMoT’s performance in forecasting South African inflation.