How credible is inflation targeting in Asia? A quantile unit root perspective

This article examines the dynamic behavior of the inflation rate for eight Asian countries using a quantile unit root test. We advocate a three-way definition of inflation targeting based on perfect, imperfect and zero credibility and advance the analysis by incorporating a fully-fledged adoption of inflation targeting. In doing so, we offer new insights by showing that the credibility of inflation targeting and the alternative monetary policy frameworks in Asia are imperfect, except for Malaysia and South Korea under a fully-fledged adoption of inflation targeting. In contrast to past studies that focus on the mean-reversion in inflation rates, we also consider trend-reversion and find that Asian inflation targeting countries have been building up their monetary policy credibility more than the non- inflation targeting countries in terms of a faster rate of decline in inflation rate changes. Our results generally indicate the presence of mean reversion at the lower quantiles only. Where stationarity is present, we find evidence of a varied speed of adjustment process across the quantiles. Finally, we determine the threshold levels whereby inflation becomes stationary and demonstrate that Asian inflation rates generally display stationary behavior during periods of inflation declining or slowing down.     

On Keynes on inflation and unemployment

Keynes tends to be represented as someone who thought that alleviating unemployment was more important than any other consideration. Interestingly it seems that this was not always the case; he did not recommend employment creation under all conditions of excess labour supply. The great inflation of World War I and its aftermath left an indelible impression on him, and this mitigated his position on the importance of high levels of employment. In 1920 he recommended that inflation in the UK be controlled even if some unemployment would result, and there is at least some hint in his work that the relative importance to him of inflation and unemployment did not vary much over the remainder of his life.     

Experts,firms, consumers or even hard data? Forecasting employment in Germany

In this article, we forecast employment growth for Germany with data for the period from November 2008 to November 2015. Hutter and Weber (2015) introduced an innovative unemployment indicator and evaluated the performance of several leading indicators, including the Ifo Employment Barometer (IEB), to predict unemployment changes. Since the IEB focuses on employment growth instead of unemployment developments, we mirror the study by Hutter and Weber (2015). It turns out that in our case, and in contrast to their article, the IEB outperforms their newly developed indicator. Additionally, consumers’ unemployment expectations and hard data such as new orders exhibit a high forecasting accuracy.     

Combining multiple probability predictions using a simple logit model

This paper begins by presenting a simple model of the way in which experts estimate probabilities. The model is then used to construct a likelihood-based aggregation formula for combining multiple probability forecasts. The resulting aggregator has a simple analytical form that depends on a single, easily-interpretable parameter. This makes it computationally simple, attractive for further development, and robust against overfitting. Based on a large-scale dataset in which over 1300 experts tried to predict 69 geopolitical events, our aggregator is found to be superior to several widely-used aggregation algorithms.     

The effects of oil price shocks on inflation in the G7 countries

This study examines the effects of three types of oil price shocks on inflation in the G7 countries with a new method of isolating oil price shocks. Based on monthly data from January 1997 to January 2019, we find that each oil price shock has the largest effect on U.S. inflation among the G7 countries and each country’s response to oil price shocks is different. Moreover, a rolling-window analysis shows that supply shocks, demand shocks and risk shocks have dynamic effects on inflation. The effect of supply shocks on inflation is strong before the financial crisis, but weakens during the crisis. However, the effect of demand shocks increases sharply in this time. The effect of risk shocks mainly occurs during the financial crisis and the European debt crisis. In addition, this study uses two ways to verify the robustness of the results. Our empirical results have important implications for policymakers and manufacturers, since the results provide a good explanation for the response of inflation in the G7 countries to the oil price shocks from different sources.     

Inflation and inflation uncertainty in China

The study examines the relationship between inflation and inflation uncertainty in China using Generalized Autoregressive Conditional Heteroscedasticity model. Particularly, this link is investigated in China’s urban and rural sectors, motivated by the substantial urban–rural divide. The results provide strong statistical supportive evidence that higher inflation raises inflation uncertainty. On the other hand, evidence on the effect of inflation uncertainty on inflation is mixed depending on the sample periods and areas examined. The understanding of inflation-uncertainty nexus in China could provide implications to policymakers in the adoption of monetary policies.     

Five dimensions of the uncertainty–disagreement linkage

We analyze the relationship between forecaster disagreement and macroeconomic uncertainty in the Euro area using data from the European Central Bank’s Survey of Professional Forecasters for the period 1999Q1–2018Q4 and find that disagreement is generally a poor proxy for uncertainty. However, the strength of this link varies with the dispersion statistic employed, the choice of either the point forecasts or the histogram means for calculating disagreement, the outcome variable considered and the forecast horizon. In contrast, distributional assumptions do not appear to be very influential. The relationship is weaker in subsamples before and after the outbreak of the Great Recession. Accounting for the forecasters’ entry to and exit from the survey has little impact on the results. We also show that survey-based uncertainty is associated with overall policy uncertainty, whereas forecaster disagreement is related more closely to the expected fluctuations on financial markets.     

Evaluating quantile forecasts in the M5 uncertainty competition

Probabilistic forecasts are necessary for robust decisions in the face of uncertainty. The M5 Uncertainty competition required participating teams to forecast nine quantiles for unit sales of various products at various aggregation levels and for different time horizons. This paper evaluates the forecasting performance of the quantile forecasts at different aggregation levels and at different quantile levels. We contrast this with some theoretical predictions, and discuss potential implications and promising future research directions for the practice of probabilistic forecasting.     

The impact of macroeconomic factors on income inequality: Evidence from the BRICS

In this paper we investigate how the evolution of income growth, real interest rates, and inflation have driven income inequality across a variety of countries with particular focus on the BRICS economies (Brazil, Russia, India, China, and South Africa) during the period 2001 to 2015. Our work suggests that, when central banks of the BRICS economies use monetary policy for macroeconomic stabilization, they need to consider the impact monetary policy changes have on the distribution of income in their nations. Our estimates reveal that the unintended consequence of policies that induce economic growth and higher prices is higher income inequality. We find that the positive relationship between the three macroeconomic variables and income inequality for the BRICS economies is stronger during the post-2008 period.     

The impact of the COVID-19 pandemic on business expectations

We document and evaluate how businesses are reacting to the COVID-19 crisis through August 2020. First, on net, firms see the shock (thus far) largely as a demand rather than supply shock. A greater share of firms report significant or severe disruptions to sales activity than to supply chains. We compare these measures of disruption to their expected changes in selling prices and find that, even for firms that report supply chain disruptions, they expect to lower near-term selling prices on average. We also show that firms are engaging in wage cuts and expect to trim wages further before the end of 2020. These cuts stem from firms that have been disproportionally negatively impacted by the pandemic. Second, firms (like professional forecasters) have responded to the COVID-19 pandemic by lowering their one-year-ahead inflation expectations. These responses stand in stark contrast to that of household inflation expectations (as measured by the University of Michigan or the New York Fed). Indeed, firms’ one-year-ahead inflation expectations fell precipitously (to a series low) following the onset of the pandemic, while household measures of inflation expectations jumped markedly. Third, despite the dramatic decline in firms’ near-term inflation expectations, their longer-run inflation expectations have remained relatively stable.