Forecasting Inflation in Emerging Markets by Using the Phillips Curve and Alternative Time Series Models

Önder, A. Özlem

doi:10.1080/1540496x.2004.11052566

Cited by 27 publications

(11 citation statements)

References 22 publications

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“…There is a growing consensus that theoretical models are more accurate in forecasting when the economy is weak, especially during periods of economic crises, compared with ARIMA, Naïve and VAR models (Buelens, 2012;Dotsey, Fujita, & Stark, 2011;Onder, 2004). For example, Onder (2004) used quarterly data between 1987: q1 and 1999: q4 to forecast Turkish inflation with the Phillips curve, ARIMA, Vector Autoregression (VAR), VECM and naive models. The evidence revealed that the Phillips curve model outperformed other models for one-quarter ahead forecasts and the prediction of the 2001 financial crisis.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A few studies also found Multivariate VAR model produce a better forecast than alternative models over the long horizon (Canova, 2007;Onder, 2004;Fritzer, Moser, & Scharler, 2002;Fanchon & Wendel, 1992). For example, Gupta, Eyden, and Waal (2015) examine whether the global vector autoregressive (GVAR) approach forecasts better than a vector error correction model (VECM) and a BVAR model for two key South African variables, GDP output and inflation between the period 1979q2-2009q4.…”

Section: Literature Reviewmentioning

confidence: 99%

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Comparing Multivariate Models’ Forecasts of Inflation for Brics and Opec Countries

Ajayi

2019

Business, Management and Education

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Purpose – This study identifies the most appropriately selected multivariate model for forecasting inflation in different economic environments. In specifying the multivariate models, the study test for the orders of integration of variables and for those that are nonstationary. For non-stationary variables, this study examines whether they are cointegrated. Engle and Granger (1987) establish that a cointegrating equation can be represented as an error correction model that incorporates both changes and levels of variables such that all of the elements are stationary. However, VARs estimated with cointegrated data will be misspecified if all of the data are differenced because long-run information will be omitted, and will have omitted stationarity inducing constraints if all the data are used in levels. Further, including variables in both levels and differences should sat-isfy stationarity requirements. However, they will omit cointegrating restrictions that may improve the model. Of course, these constraints will be satisfied asymptotically; but efficiency gains and improved multi-step forecasts may be achieved by imposing the constraints (Engle and Granger 1987, p. 259). Therefore, this study test for order of integration and compare inflation forecasting performance of different multivariate models for BRICS and OPEC countries. Research methodology – The following approaches were considered; the first approach is to construct a VAR model in differences (stationary form) to forecast inflation. The second approach is to construct a VECM without imposing cointegrating restrictions. The third approach is to construct a VEC that imposes cointegrating restrictions on the VECM. This will help to understand whether imposing cointegrating restrictions via a VEC improves long-run forecasts. Research limitation – The proposed multivariate models focused on differencing and cointegrating restrictions to ensure the stationarity of the data, the available variables were combined and specified based on their level of integration to forecast inflation. For instance, a VAR model is estimated based on differenced variables I(0); the same holds true for VECM and VEC models, where differenced variables and linear combinations of I(I) covariates are stationary. In future, multivariate models guided by economic theory rather than the order of integration of variables are suggested. Findings – The result shows that the forecast performance of inflation depends on the nature of the economy and whether the country experiencing higher inflation or low inflation. For instance, the model that includes long-run information in the form of a specified cointegrated equation generally improves the inflation forecasting performance for BRICS countries and one OPEC country (Saudi Arabia) that has a history of low inflation. Practical implications – This research will improve the policy makers decision on how to select appropriate model to forecast inflation over different economic environment. Originality/Value – These methods have not been used to forecast inflation for many emerging economies such as OPEC and BRICS countries despite the importance of many of these countries to the global economy. This study fills this gap by evaluating the forecasting performance of inflation using multivariate VAR and cointegrating models for OPEC and BRICS economies.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Comparing Multivariate Models’ Forecasts of Inflation for Brics and Opec Countries

Ajayi

2019

Business, Management and Education

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“…Second, there is some debate on whether the Phillips Curve trade-off exists in Turkey (e.g. Kuştepeli, 2005;Onder, 2004Onder, , 2009. We hypothesize that this debate may reflect the difficulty in establishing a Phillips Curve if strong distributional effects from relative price changes are omitted from the model.…”

Section: Introductionmentioning

confidence: 95%

“…The literature on the Phillips Curve relates inflation to output or unemployment gaps (e.g. Onder, 2004Onder, , 2009Kuştepeli, 2005;de Mendonça, 2009). The literature on relative price variability relates inflation to the second and third moments of relative price changes (e.g.…”

Section: Introductionmentioning

confidence: 99%

Relative price variability and the Phillips Curve: evidence from Turkey

Çatık

Martin

Önder

2011

Journal of Economic Studies

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We argue that relative price changes are a key component of the Phillips curve relationship between inflation and output. Building on work by Ball and Mankiw, we propose including measures of the variances and skewness of relative price adjustment in an otherwise standard model of the Phillips curve. We examine the case of Turkey, where distribution of price changes is especially skewed and where the existence of a Phillips curve has been questioned. We have two main findings: (i) inclusion of measures of the distribution of relative price changes improves our understanding of the Phillips curve trade-off; (ii) there is no evidence of such a trade-off if these measures are not included.

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“…Twenty-five years after Phillips's paper, Robert Lucas and Thomas Sargent set the simultaneously high inflation and unemploymentevident across practically all developed economies -against a Phillips curve backdrop and decried the econometric failure on a grand scale. This followed a sequence of papers during the 1970s that had both supported and called into question the econometric and theoretical basis of the Phillips curve and hence its usefulness for public policy purposes (Lipsey, 1960;Solow, 1970;Onder, 2004 andFaridul et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Does Philips Relations Really Exist in Nigeria? Empirical Evidence

Ojapinwa¹,

Esan²

2013

IJEF

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The paper examines the existence and the stability of Phillips relations for Nigeria, using time series data from 1970 to 2010. Graphical, Augmented Dickey Fuller and Philip Peron unit root tests were employed to check for stationarity. ARDL and DOLS general to specific approaches to cointegration have been used to explore the Philips relations and ECM to understand short run dynamics. The estimates shows that relation between the change in inflation rate and the unemployment rate is theoretically negative in the short run-a low unemployment rate leads to an increase in the inflation rate and therefore an acceleration of the price levelhowever, the relation became non existence in the long run with positive relationship between inflation and unemployment signifying stagflation. Meanwhile, recursive residual, CUSUM and CUSUMsq tests confirm a stable Philips relation.

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Forecasting Inflation in Emerging Markets by Using the Phillips Curve and Alternative Time Series Models

Cited by 27 publications

References 22 publications

Comparing Multivariate Models’ Forecasts of Inflation for Brics and Opec Countries

Comparing Multivariate Models’ Forecasts of Inflation for Brics and Opec Countries

Relative price variability and the Phillips Curve: evidence from Turkey

Does Philips Relations Really Exist in Nigeria? Empirical Evidence

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