scholarly journals The term structure, leading indicators, and recessions: evidence from Switzerland, 1974–2017

2020 ◽  
Vol 156 (1) ◽  
Author(s):  
Rebecca Stuart
Keyword(s):  
Term Structure ◽  
Predictive Power ◽  
Leading Indicators ◽  
Monthly Data ◽  
Monetary Aggregates ◽  
Probit Models ◽  
Out Of Sample ◽  
Business Course ◽  
Dynamic Probit Models

AbstractThis paper studies the predictive power for recessions of the slope of the Swiss term structure using monthly data for 1974–2017. Dynamic probit models indicate that the term structure contains information useful for predicting recessions for horizons up to 19 months. Whether the economy is currently in recession or not is also useful for forecasting recessions. These relationships prove stable over the sample. Robustness tests indicate that the KOF business course indicator and some monetary aggregates contain different information from the term structure which can improve the in- and out-of-sample fit of the model.

scholarly journals Forecasting Macedonian Business Cycle Turning Points Using Qual Var Model

2016 ◽  
Vol 5 (3) ◽  
pp. 61-78
Author(s):  
Magdalena Petrovska ◽  
Aneta Krstevska ◽  
Nikola Naumovski
Keyword(s):  
Business Cycle ◽  
Predictive Power ◽  
Turning Points ◽  
Probit Model ◽  
Economic Conditions ◽  
Var Model ◽  
Leading Indicators ◽  
Out Of Sample ◽  
The Business Cycle

Abstract This paper aims at assessing the usefulness of leading indicators in business cycle research and forecast. Initially we test the predictive power of the economic sentiment indicator (ESI) within a static probit model as a leading indicator, commonly perceived to be able to provide a reliable summary of the current economic conditions. We further proceed analyzing how well an extended set of indicators performs in forecasting turning points of the Macedonian business cycle by employing the Qual VAR approach of Dueker (2005). In continuation, we evaluate the quality of the selected indicators in pseudo-out-of-sample context. The results show that the use of survey-based indicators as a complement to macroeconomic data work satisfactory well in capturing the business cycle developments in Macedonia.

How to Hedge Against Inflation Risk in Vietnam

2021 ◽  
Author(s):  
T. Thanh-Binh Nguyen
Keyword(s):  
Predictive Power ◽  
Gold Price ◽  
Price Stability ◽  
Leading Indicators ◽  
Inflation Risk ◽  
Monthly Data ◽  
Long Run ◽  
The Us ◽  
Short Run ◽  
Us Dollar

Abstract Vietnam has experienced galloping inflation and faced serious dollarization since its reform. To effectively control its inflation for promoting price stability, it is necessary to find efficacious leading indicators and the hedging mechanism. Using monthly data over the period from January 1997 to June 2020, this study finds the predictive power and hedge effectiveness of both gold and the US dollar on inflation in the long-run and short-run within the asymmetric framework. Especially, the response of inflation to the shocks of gold price and the US dollar are quick and decisive, disclosing the sensitiveness of inflation to these two variables.

Leading Indicators of German Business Cycles. An Assessment of Properties / Frühindikatoren der deutschen Konjunktur. Eine Beurteilung ihrer Eigenschaften

2002 ◽  
Vol 222 (3) ◽  
Author(s):  
Ulrich Fritsche ◽  
Sabine Stephan
Keyword(s):  
Business Cycle ◽  
Predictive Power ◽  
Frequency Domain Analysis ◽  
Leading Indicators ◽  
Reference Series ◽  
Out Of Sample ◽  
Causality Tests ◽  
Short Run ◽  
The Business Cycle ◽  
German Data

SummaryA reliable leading indicator should possess the following properties: (1) The movements in the indicator series should resemble those in the business cycle reference series. (2) The relation between the reference series and the indicator should be statistically significant and stable over time. (3) The inclusion of the indicator in out-of-sample forecasting procedures should improve the predictive power. Our analysis deals with tests for these requirements applied to German data. We used frequency domain analysis, different Granger-causality tests and out-of sample forecasts. Only few indicators passed all tests. Their inclusion into VAR-based forecasts improves the forecast in the very short run. Further research should concentrate on the unsolved problem of the prediction of business cycle turning points.

scholarly journals Predicting the German Economy: Headline Survey Indices Under Test

2021 ◽  
Author(s):  
Robert Lehmann ◽  
Magnus Reif
Keyword(s):  
Gross Domestic Product ◽  
Private Sector ◽  
Service Sector ◽  
Predictive Power ◽  
Manufacturing Sector ◽  
German Economy ◽  
Value Added ◽  
Leading Indicators ◽  
European Research ◽  
Out Of Sample

AbstractThis analysis investigates the predictive power of the headline indices of the four most important German survey providers. We conduct an out-of-sample, real-time forecast experiment for growth of total and private sector gross domestic product and growth of gross value added in both the manufacturing and the service sector. All providers publish valuable leading indicators for both GDP measures, with some advantages for the ifo indicators and the Economic Sentiment Indicator, respectively. For the manufacturing sector, indicators provided by the ifo Institute are clearly superior. For the service sector, all indicators prove to have a similar nowcasting performance, whereas the Economic Sentiment Services of the Centre for European Research is preferable for one quarter-ahead predictions.

scholarly journals German forecasters’ narratives: How informative are German business cycle forecast reports?

2021 ◽  
Author(s):  
Karsten Müller
Keyword(s):  
Business Cycle ◽  
Fixed Effects ◽  
Predictive Power ◽  
Recursive Estimation ◽  
Regression Methods ◽  
Inflation Forecasts ◽  
Fixed Effects Panel Regression ◽  
Weak Evidence ◽  
Out Of Sample ◽  
Different Characteristics

AbstractBased on German business cycle forecast reports covering 10 German institutions for the period 1993–2017, the paper analyses the information content of German forecasters’ narratives for German business cycle forecasts. The paper applies textual analysis to convert qualitative text data into quantitative sentiment indices. First, a sentiment analysis utilizes dictionary methods and text regression methods, using recursive estimation. Next, the paper analyses the different characteristics of sentiments. In a third step, sentiment indices are used to test the efficiency of numerical forecasts. Using 12-month-ahead fixed horizon forecasts, fixed-effects panel regression results suggest some informational content of sentiment indices for growth and inflation forecasts. Finally, a forecasting exercise analyses the predictive power of sentiment indices for GDP growth and inflation. The results suggest weak evidence, at best, for in-sample and out-of-sample predictive power of the sentiment indices.

TESTING FOR WEAK SEPARABILITY USING STOCHASTIC SEMI-NONPARAMETRIC TESTS: AN EMPIRICAL STUDY ON US DATA

2017 ◽  
Vol 22 (6) ◽  
pp. 1510-1534
Author(s):  
Ryan S. Mattson ◽  
Philippe de Peretti
Keyword(s):  
Empirical Study ◽  
Financial Stability ◽  
Nonparametric Tests ◽  
Extended Version ◽  
Monthly Data ◽  
Monetary Aggregates ◽  
Separability Criterion ◽  
Weak Separability ◽  
Existence Conditions ◽  
Necessary Existence

In this paper, we use the weak separability criterion to check for the existence of six different monetary aggregates reported by the Center of Financial Stability (CFS). We implement an extended version of the semi-nonparametric tests introduced by Barnett and de Peretti on US monthly data from January 1967 to December 2012. The test, first, checks for the necessary existence conditions of an overall utility function and a monetary subutility function, and then tests for the separability of the latter. On different subsamples, our results suggest that only the DM1 aggregate meets the separability criterion. Implemented on macroeconomic data, we have tested a joint assumption about separability and the existence of a representative agent. Thus, the rejection of the null could also be due to the rejection of stringent Gorman's conditions. More advanced tests for weak separability are clearly required to confirm the results found in this paper.

Testing the predictive power of the term structure without data snooping bias

2013 ◽  
Vol 121 (3) ◽  
pp. 546-549 ◽  
Author(s):  
Yi-Cheng Kao ◽  
Chung-Ming Kuan ◽  
Shikuan Chen
Keyword(s):  
Term Structure ◽  
Predictive Power ◽  
Data Snooping
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