Modeling and forecasting inflation in Japan

by Sekine Toshitaka

Publisher: International Monetary Fund, Policy Development and Review Department in [Washington, D.C.]

Written in English
Published: Pages: 34 Downloads: 210
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  • Inflation (Finance) -- Japan -- Forecasting -- Econometric models.

Edition Notes

StatementToshitaka Sekine.
GenreEconometric models.
SeriesIMF working paper -- WP/01/82
ContributionsInternational Monetary Fund. Policy Development and Review Dept.
The Physical Object
Pagination34 p. :
Number of Pages34
ID Numbers
Open LibraryOL18979079M

This article aims at modeling and forecasting inflation in Pakistan. For this purpose a number of econometric approaches are implemented and their results are compared. An Econometric Model of Inflation in India Bhowmik International Institute for Development Studies, Kolkata Abstract- The paper verified that the inflation model in India is cointegrated in the order I(1) considering GDP growth rate, degree of openness, growth rate of money supply, nominalFile Size: KB. Modeling the United States Economy Open Script This example illustrates the use of a vector error-correction (VEC) model as a linear alternative to the Smets-Wouters Dynamic Stochastic General Equilibrium (DSGE) macroeconomic model, and applies many of the techniques of Smets-Wouters to the description of the United States g: Japan. Get this from a library! Real-time estimation of the output gap in Japan and its usefulness for inflation forecasting and policymaking. [Koichiro Kamada].

Forecasting for the Pharmaceutical Industry Models for New Product and In-Market Forecasting and How to Use Them A catalogue record for this book is available from the British Library ISBN: 1 0 (hbk) New Product Forecast Algorithm 41 Modeling the Market 42 Forecasting . The effects of inflation on economic growth and on its macroeconomic determinants Muhammad Khan To cite this version: Muhammad Khan. The effects of inflation on economic growth and on its macroeconomic deter-minants. Economics and Finance. Université d’Orléans, English. ￿NNT: ORLE￿. ￿tel￿Missing: Japan. The literature studying inflation modeling and forecasting, in particular for the U.S., has acknowledged the role of global economic conditions in understanding domestic inflation only recently (even though globalization itself is not a recent phenomenon). This book provides new insights into the modeling and forecasting of primary commodity prices by featuring comprehensive applications of the most recent methods of statistical time series analysis. The latter utilize econometric methods concerned with structural breaks, unobserved components, chaotic discovery, long memory, heteroskedasticity Reviews: 2.

Forecasting inflation can be approached in different ways: a) time series models; b) leading indicator models; and c) congruent models (Hendry ). The disaggregated analysis can be applied with each type of models. When using models with explanatory variables, the disaggregation allows specific effects of the commonMissing: Japan.

Modeling and forecasting inflation in Japan by Sekine Toshitaka Download PDF EPUB FB2

This paper estimates an inflation function and forecasts one-year ahead inflation for Japan. It finds that (i) markup relationships, excess money and the output gap are particularly relevant long-run determinants for an equilibrium correction model (EqCM) of inflation; (ii) with intercept corrections, one-year ahead inflation forecast performance of the EqCM is good; and (iii) forecast.

Get this from a library. Modeling and forecasting inflation in Japan. [Toshitaka Sekine; International Monetary Fund. Policy Development and Review Department.] -- This paper estimates an inflation function and forecasts one-year ahead inflation for Japan. It finds that (i) markup relationships, excess money and the output gap are particularly relevant long-run.

Title: Modeling and Forecasting Inflation in Japan - WP/01/82 Created Date: 6/21/ AM. Downloadable. This paper estimates an inflation function and forecasts one-year ahead inflation for Japan. It finds that (i) markup relationships, excess money and the output gap are particularly relevant long-run determinants for an equilibrium correction model (EqCM) Modeling and forecasting inflation in Japan book inflation; (ii) with intercept corrections, one-year ahead inflation forecast performance of the EqCM is good; and (iii.

Later inSekine () forecast the inflation of Japan and concluded that for determining the inflation equilibrium correction model, there could be addition of some variables like excess.

While it is nigh on impossible to forecast long-term inflation, there are currently arguments in favour of adding marginal protection against inflation to a portfolio.

Inflation-linked bonds, gold, infrastructure and real estate are among asset classes that have typically provided the best hedge against inflation. The statistic shows the inflation rate in Japan from towith projections up until The inflation rate is calculated using the price increase of a defined product basket.

Moreover, empirical literature related to inflation modeling and forecasting in different countries was analyzed. When talking about inflation in transition economies, it is absolutely important to be aware that inflation is a very complex phenomenon that touches upon other aspects of socio-economic and political developments.

To reveal some long. Introduction. Forecasting is a key activity for policy makers. Given the possible complexity of the processes underlying policy targets, such as inflation, output gaps, or employment, and the difficulty of forecasting in real-time, recourse is often taken to simple by: Autoregressive integrated moving average (ARIMA) models to forecasting inflation in Ireland.

Meyler et al (a) used Bayesian method to estimate vector autoregressive (VAR) models to forecast inflation in Ireland. Salam () employed ARIMA models on the Pakistan inflation data to find the best model to forecast inflation. Short-term inflation forecasting for monetary policy in Nigeria, central Bank of Nigeria Occasion Paper No.

42; Asel ISAKOVA (). Modeling and Forecasting inflation in developing Countries: The case of Economies in Central Asia. Discussion Paper No. ; Prapanana M, Labani S. and Saptarsi G. Stock and Watson: w Modeling Inflation After the Crisis: Stock and Watson: w Why Has U.S.

Inflation Become Harder to Forecast?: Bernanke, Boivin, and Eliasz: w Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach: Ang, Bekaert, and Wei: w Do Macro Variables, Asset Markets or Surveys Forecast Inflation Better. Time Series Modeling and Forecasting Inflation: Evidence from Nigeria The International Journal of Business and Finance Research, Vol.

8 (2) pp.12 Pages Posted: 2 Feb Cited by: 2. This book is the result of the effort of many people. Daniel Alvarez-Estrada was the first Appendix: A Revenue Forecasting Model for the Mexican VAT 9. Excise Tax Models Introduction Impact of the Excise in the Single Market rate, the rate of inflation, and other macroeconomic variables.

Revenue estimates areMissing: Japan. This paper aims at modeling and forecasting real GDP rate in Greece. For this purpose using the Box- Jenkins methodology during the period with one ARIMA (1,1,1) model.

Using this model, we forecast the values of real GDP rate forand Statistical resultsFile Size: KB. Macroeconomic Modeling and Inflation-Rate Forecasting at the Reserve Bank of New Zealand. By Jaromir Benes, International Monetary Fund.

The primary function of the Reserve Bank of New Zealand (RBNZ) is to formulate and implement monetary policy to maintain price stability. To fulfill its legislative mandate, the RBNZ is committed to keeping.

autoregressive integrated moving average (ARIMA) time series models for forecasting Pakistan’s inflation. A framework for ARIMA forecasting is drawn up. On the basis of in-sample and out-of-sample forecast it can be concluded that the model has sufficient predictive powers and the findings are well in line with those of other Size: KB.

Japan: Inflation and labour market • The headline and core CPI have both moved into clearly positive territory in recent months • Import prices have been a key factor driving up inflation; domestically-generated inflation is more subdued • The labour market has proved surprisingly strong in recent months and some indicators suggest.

serious forecasting models. Finally, the creation of a number of vintage datasets in recent years makes possible quasi-realtime comparisons of proposed methods.

By a quasi-realtime forecast we mean a model-based forecast for some point in time in the past based only on data that was available to forecasters at that Size: KB.

Introduction to Time Series Data and Serial Correlation (SW Section ) First, some notation and terminology. Notation for time series data Y t = value of Y in period t. Data set: Y 1,Y T = T observations on the time series random variable Y We consider only consecutive, evenly-spaced observations (for example, monthly, tonoFile Size: 2MB.

Downloadable. The evolution of the rate of price inflation, and unemployment in Japan has been modeled within the Phillips curve framework.

As an extension to the Phillips curve, we represent both variables as linear functions of the change rate of labor force. All models were first estimated in for the period between and Here we update these original models with data through Inflation Reports and Models: How Well Do Central Banks Really Write.

Prepared by Aleš Bulíř, Jaromír Hurník, and Kateřina Šmídková Authorized for distribution by Ray Brooks May Abstract We offer a novel methodology for assessing the quality of inflation reports.

In contrast to the existingMissing: Japan. Models of inflation forecast and accuracy has evolved in several studies ranging from extrapolation to econometric modeling.

The early study of inflation forecast by Landsman and Damodaran () in which the univariate autoregressive integrated moving Missing: Japan. V.3 Summary: Fundamental Forecasting Steps (1) Selection of Model (for example, PPP model) used to generate the forecasts.

(2) Collection of St, Xt (in the case of PPP, exchange rates and CPI data needed.) (3) Estimation of model, if needed (regression, other methods). A number of studies show that short-term inflation forecasting (up to two years) is best carried out using simple methods, which are based on the time series of inflation alone (for example.

Start studying Chapter 6: International Parity Relationships and Forecasting Foreign Exchange Rates. Learn vocabulary, terms, and more with flashcards, games, and other study tools.

The Gross Domestic Product (GDP) is the market value of all goods and services produced within the borders of a nation in a year. In this paper, Kenya’s annual GDP data obtained from the Kenya National Bureau of statistics for the years to was studied. Gretl and SPSS 21 statistical softwares were used to build a class of ARIMA (autoregressive integrated moving average) models.

The study compares the accuracy, over the last 15 years, of three sets of inflation forecasts from NAIRU models to the naive forecast that at any date inflation will be the same over the next year.

Inflation is a key element of a national economy, and it is also a prominent and important issue influencing the whole economy in terms of marketing.

This is a complex problem requiring a large investment of time and wisdom to attain positive results. Thus, appropriate tools for forecasting inflation variables are crucial significant for policy making. In this study, both clarified value Cited by: 8.

Title: Empirical modelling and model selection for forecasting monthly inflation of ghana, Author: Alexander Decker, Name: Empirical modelling and model selection for forecasting monthly inflation Missing: Japan. Mathematical Theory and Modeling ISSN (Paper) ISSN (Online) Vol.4, No.3, Empirical Modelling and Model Selection for Forecasting Monthly Inflation Missing: Japan.Forecasting Inflation James H.

Stock and Mark W. Watson NBER Working Paper No. March JELNo. E31,C32 ABSTRACT This paper investigates forecasts of U.S. inflation at the month horizon. The starting point is the conventional unemployment rate Phillips curve, which is examined in a simulated out of sample forecasting Size: KB.STOCHASTIC MODELS FOR INFLATION, INVESTMENTS AND EXCHANGE RATES A D Wilkie, United Kingdom This paper was first presented at a Conference on "Forecasting Inflation and Investment Returns" organised by the Canadian Institute of Actuaries in Toronto, 2nd-3rd Decemberand is reproduced with permission of the Canadian Size: KB.