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.

The relative importance of survey-based, VAR-based or myopic expectations is evaluated in accounting for US inflation dynamics in a New Keynesian Phillips Curve (NKPC) setting. Our contribution is threefold. First, we estimate the NKPC with both final and real-time vintage data in order to control for large revisions in the real GDP data. Second, we distinguish between two different series for VAR-based inflation forecasts—derived by a recursive or rolling-window method—to account for changes in the conduct and transmission mechanisms of US monetary policy after World War II. Third, joint restrictions are tested in the NKPC to assess whether one of the expectational variables is able, on its own, to capture inflation dynamics. On a statistical basis, we find that there is no clear-cut winner between VAR- and survey-based inflation expectations. Most of our estimated NKPC variants conclude that survey inflation expectations tend to have the largest numerical weight. Nevertheless, the difference between VAR- and survey-based expectations’ estimated coefficients is not statistically significant. Moreover, myopic expectations do not play any significant role in the majority of the estimated NKPC variants.

In this paper we analyze whether a news-based measure of financial stress index (FSI) in the US can predict West Texas Intermediate oil returns and (realized) volatility over the monthly period of 1889:01 to 2016:12, using a dynamic conditional correlation multivariate generalized auto-regressive 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 FSI to oil returns and volatility cannot be considered reliable. When we use the DCC-MGARCH model, which is robust to such misspecifications, in 75 percent and 80 percent of the sample periods, FSI in fact do strongly predict the oil returns and volatility respectively. Overall, our results highlight that FSI is helpful in predicting oil returns and volatility, when one accounts for nonlinearity and regime changes through a robust time-varying model.

We analyse the dynamics of the causal interaction between the stock and foreign exchange markets for the United Kingdom using monthly data going as far back as 1791. First, we consider static causality tests, yielding mixed results. Given the evidence of structural breaks in the relationship between equity and currency returns, we use next the Dynamic Conditional Correlation-Multivariate Generalised Autoregressive Conditional Heteroskedasticity time-varying tests for Granger causality. The time-varying testing strategy we implement allows us to detect whether any causal relationship exists at each point in time between stock price and exchange rates returns. We find overwhelming evidence of time-varying information spillovers between the equity and currency returns. We check the robustness of our findings by running the entire battery of tests for two emerging market economies, namely, India and South Africa starting in 1920 and 1910 respectively. On the whole, the United Kingdom results are comparable to those in India and South Africa. As such, our results encompass the fragmented findings from our static tests as well as those in the extant literature.

ABSTRACT 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.

The association between oil prices and inflation has remained an intriguing issue for media, academic as well as policy enquiry. Against this backdrop, we perform the frequency-domain causality test to investigate whether the growth rate of oil prices has predictive content for inflation in South Africa. As a preliminary step in our analysis, given that we use a long historical data set spanning from 1922:M01 to 2013:M07, we investigate the possibility of structural breaks in the inflation equation. We detect three breaks which define four regimes. We then perform the frequency-domain test on the full-sample, as well as, the four identified regime-specific subsamples. We find evidence of the growth rate of oil prices to have predictive content for South African inflation based on the full-sample, as well as, two of the four regime-specific sub-samples. Given that the frequency-domain test allows us to decompose the causality across different time horizons, results also suggest that cycles of predictability of South African inflation emanating from the the growth in international oil prices could last for much longer durations for periods preceding the adoption of an inflation-targeting framework for monetary policy in South Africa. - La relazione tra prezzo del petrolio e inflazione e un problema di grande interesse sia per i media sia per la ricerca accademica e politica. Sulla base di questa considerazione abbiamo eseguito il test di causalita basato sulla frequenza per esaminare se l’aumento del prezzo del petrolio e predittivo dell’inflazione in Sud Africa. Come primo passo nell’analisi, premesso che utilizziamo un data set storico ampio – gennaio 1922-luglio 2013 – esaminiamo la possibilita di break strutturali nell’equazione di inflazione. Rileviamo tre break che definiscono quattro regimi. In seguito eseguiamo il test basato sulla frequenza sia sul campione completo che sui quattro sotto-campioni di specifici regimi. I risultati evidenziano che il tasso di aumento dei prezzi del petrolio e predittivo dell’inflazione in Sud Africa sulla base sia del campione completo che di due dei quattro sotto-campioni di specifici regimi. Considerato che il test basato sulla frequenza ci consente di scomporre la causalita per orizzonti temporali differenti, i risultati suggeriscono anche che i cicli di prevedibilita dell’inflazione in Sud Africa derivanti dalle variazioni dei prezzi internazionali del petrolio potrebbero essere molto piu duraturi in periodi che precedono l’adozione di un obiettivo di politica monetaria inflation-targeting.

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.

The real interest rate is a very important variable in the transmission of monetary policy. It features in vast majority of financial and macroeconomic models. Though the theoretical importance of the real interest rate has generated a sizable literature that examines its long-run properties, surprisingly, there does not exist any study that delves into this issue for South Africa. Given this, using quarterly data (1960:Q2-2010:Q4) for South Africa, our paper endeavors to analyze the long-run properties of the ex post real rate by using tests of unit root, cointegration, fractional integration and structural breaks. In addition, we also analyze whether monetary shocks contribute to fluctuations in the real interest rate based on test of structural breaks of the rate of inflation, as well as, Bayesian change point analysis. Based on the tests conducted, we conclude that the South African EPPR can be best viewed as a very persistent but ultimately mean-reverting process. Also, the persistence in the real interest rate can be tentatively considered as a monetary phenomenon.

Following the 2007-2009 global recession, economic policy uncertainty and its effect on economic recovery has become an issue of interest in academic, media as well as policy-making circles (Baker et al., 2013). Given this backdrop, we investigate causality between economic policy uncertainty in some of the world's major economies using the economic policy uncertainty index developed by Baker et al. (2013). We implement both the traditional linear and the nonlinear variants of the Granger causality test. Based on the Diks and Panchenko (2005) non-linear Granger causality test, we find significant evidence of bidirectional causality between countries' economic policy uncertainty across the sample. The results are consistent with the fact that the global economy has become more integrated through trade, financial and confidence linkages. Also, our findings highlight that inference from traditional (linear) Granger causality test can be misleading in the presence of non-linearity in the data.

Inflation forecasts are a key ingredient for monetary policymaking 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,e.g. such as alternative measures of inflation that might be of interest to policymakers, 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 2000Q1-2011Q4. The hybrid DSGE performs extremely well in forecasting inflation variables (both core and non-modeled) in comparison with forecasts reported by other models such as AR(1).

This paper investigates the existence of significant spillovers from the housing sector onto the wider economy for the seven major OECD countries using Uhlig's (2005) agnostic identification procedure. This method allows a housing demand shock to be identified in a six-variable VAR model by imposing sign restrictions on the impulse responses of consumer prices, residential investment, real house prices and mortgage loans, while private consumption and nominal interest rate responses are left unrestricted. The results suggest that consumption responds positively and significantly to a house price shock in Canada, France, Japan and the UK. A significant positive delayed response of nominal interest rates follows a house price shock in Germany, Japan, the UK and the US, suggesting that while central banks do not seem to respond instantly and systematically to a housing demand shock, their repercussions on the economy tend to translate into higher policy rates after a few quarters. Les prix des logements affectent-ils la consommation et le taux d'interet ? : Une etude empirique sur des pays de l'OCDE utilisant une procedure d'identification agnostique Cet article etudie l'existence d’une inflence significative du secteur du logement sur l'economie dans son ensemble pour les sept grands pays de l’OCDE, en utilisant la procedure d'identification agnostique d’Uhlig (2005). Cette methode permet l'identification d'un choc de demande de logement dans un modele VAR a six variables en imposant des restrictions sur les signes des fonctions de reaction aux innovations des prix a la consommation, de l'investissement residentiel, des prix reels des logements et des prets hypothecaires, tandis que les reponses de la consommation privee et des taux d'interet nominaux sont laissees libres. Les resultats suggerent que la consommation reagit positivement et significativement a un choc de prix des logements au Canada, en France, au Japon et au Royaume-Uni. D'autre part, une reponse positive, significative et retardee des taux d'interet nominaux suit un choc de prix des logements en Allemagne, au Japon, au Royaume-Uni et aux Etats-Unis, suggerant que si les banques centrales ne semblent pas reagir instantanement et systematiquement a un choc de demande de logement, les repercussions de ce dernier sur l'economie ont tendance a se traduire par des taux directeurs plus eleves apres quelques trimestres.

This study tests for house price bubbles in the South African housing market using quarterly data from 1969:Q2 to 2009:Q3, based on the unit root test developed by Phillips, Wu, and Yu (2010). The findings indicate house price bubbles in the aggregate, large, medium, and small-middle segments, but not in the luxury and affordable segments. Next, symmetric and asymmetric versions of an Error Correction Model (ECM) are used to investigate the spillover effects from the housing sector onto consumption. Results indicate significant and asymmetric spillovers, with consumption responding significantly to house price deceleration, although there is no evidence of the effect being higher during the bubble period.

This study investigates the trade effects of the EU-SA and SADC preferential trade agreements of which South Africa is a member. Using a panel data estimation of the gravity model of bilateral trade and based on data from 1994 to 2008, the study finds the EU-SA preferential trade agreement to have a significant trade expansion effect. The study further reveals that an informative conclusion on trade effects of the SADC preferential trade agreement can only be reached once the agreement has been fully operational. The study also recommends that trade policy in South Africa should increasingly be geared towards broad-based multilateral liberalisation. In addition, South Africa should promote regional economic stability and development through supporting regional trade agreements initiatives. Keywords: Trade creation, trade diversion, preferential trade agreement, panel data estimation, gravity model of bilateral trade

This paper tests for house price bubbles in the South African housing market, using quarterly data from 1969:Q2 to 2009:Q3, based on the unit root test developed by Phillips et al. 2010. This test allows us to detect whether a bubble exists or not, as well as the date of emergence and collapse of the same. Our findings show evidence of house price bubbles in the large, medium and small-middle segments, as well as, the aggregate middle-segment of the South African housing market. There is however, no evidence of bubbles in the luxury and affordable segments of the market. Next we estimate an Error Correction Model (ECM) to investigate the existence of spillover effects from the housing sector onto consumption. Results indicate significant spillovers, though there is no evidence of the effect being higher during the bubble period. Finally, we disentangle the effects of the house price acceleration and deceleration on consumption in an effort to investigate whether or not consumption reacts asymmetrically to movements in house prices. We find that consumption responds significantly to the house price deceleration but not to acceleration, with this effect also not showing any evidence of being higher during the identified bubble period. The fact that we do not observe consumption to be more responsive to house price acceleration (deceleration) during the bubble period is most likely due two reasons: First, the National Credit Act number 34 implemented in 2005, which enforced responsible granting and use of credit and prohibited reckless awarding of credits (NCA, 2006) and second, the findings of recent studies depicting evidence of pronounced discretionary changes by the South African Reserve Bank to counter the recent adverse movements in the financial markets.