scholarly journals SURVEY MEASURES OF INFLATION EXPECTATION

2012 ◽  
Vol 14 (4) ◽  
pp. 421-456
Author(s):  
Endy Dwi Tjahjono ◽  
Harmanta Harmanta ◽  
Nur M. Adhi Purwato
Keyword(s):  
Inflation Rate ◽  
Forecast Horizon ◽  
Directional Information ◽  
Economic Agents ◽  
Inflation Expectation ◽  
Vector Auto Regression ◽  
Short Horizon ◽  
Auto Regression ◽  
Forward Looking

The research objective was to analyze various survey measures of inflation expectation in Indonesia. We found that the heterogeneity of inflation expectationamong economic agents and professional forecastersfor short forecast horizon is very low. Survey measures of inflation expectation appear to be forward looking, but only for relatively short horizon. Although the magnitude and length vary across measures of inflation expectation, we find that shock to inflation expectation significantly affect the dynamics of the actual inflation rate. Based on the accuracy, the effect on actual inflation and directional information that they have in predicting current and future inflation, inflation expectation from Consensus Forecast outperformed the others.Keywords: Inflation expectation, Vector Auto Regression, balanced score.JEL Classification: C42, E31.

scholarly journals SURVEY MEASURES OF INFLATION EXPECTATION

2012 ◽  
Vol 14 (4) ◽  
pp. 397-432
Author(s):  
Endy Dwi Tjahjono ◽  
Harmanta Harmanta ◽  
Nur M. Adhi Purwato
Keyword(s):  
Inflation Rate ◽  
Forecast Horizon ◽  
Directional Information ◽  
Economic Agents ◽  
Inflation Expectation ◽  
Vector Auto Regression ◽  
Short Horizon ◽  
Auto Regression ◽  
Forward Looking

The research objective was to analyze various survey measures of inflation expectation in Indonesia. We found that the heterogeneity of inflation expectationamong economic agents and professional forecastersfor short forecast horizon is very low. Survey measures of inflation expectation appear to be forward looking, but only for relatively short horizon. Although the magnitude and length vary across measures of inflation expectation, we find that shock to inflation expectation significantly affect the dynamics of the actual inflation rate. Based on the accuracy, the effect on actual inflation and directional information that they have in predicting current and future inflation, inflation expectation from Consensus Forecast outperformed the others. Keywords: Inflation expectation, Vector Auto Regression, balanced score.JEL Classification: C42, E31

scholarly journals Is Inflation Target Announced by Bank Indonesia the Most Accurate Inflation Forecast?

2016 ◽  
Vol 62 (2) ◽  
pp. 98 ◽  
Author(s):  
Faisal Rachman
Keyword(s):  
Inflation Rate ◽  
Multivariate Time Series ◽  
Accurate Method ◽  
Time Series Models ◽  
Inflation Target ◽  
Evaluation Period ◽  
Inflation Expectation ◽  
Out Of Sample ◽  
Inflation Targets ◽  
Forward Looking

This article investigates whether following Bank Indonesia’s explicit inflation targets (forward-looking) is a more accurate method of predicting inflation rate in Indonesia than forecast methods utilizing past information of macroeconomic data (backward-looking). The analysis is conducted by performing naive, univariate, and multivariate time-series models with an out-of-sample forecast evaluation period of January 2014–December 2016. It is found that the backward-looking approach outperforms the forward-looking approach at all forecast horizons, indicating that Bank Indonesia still does not succeed to anchor inflation expectation towards the desired level.AbstrakArtikel ini mencoba untuk meneliti apakah mengikuti target inflasi yang dikeluarkan oleh Bank Indonesia (forward-looking) adalah metode yang lebih akurat untuk memprediksi tingkat inflasi suatu periode tertentu di Indonesia ketimbang metode peramalan inflasi dengan menggunakan data informasi makroekonomi lampau (backward-looking). Analisa dilakukan dengan membandingkan model runtun waktu naif, satu peubah, dan peubah ganda dengan periode Januari 2014–Desember 2016 digunakan sebagai periode evaluasi sampel peramalan. Tulisan ini menyimpulkan bahwa performa peramalan metode backward-looking lebih unggul dari pada metode forward-looking untuk setiap jangka waktu peramalan yang mengindikasikan bahwa Bank Indonesia masih belum berhasil dalam mengendalikan ekspektasi publik terhadap inflasi ketingkat yang diinginkan.Kata kunci: Inflasi; Forward-Looking; Backward-Looking; ARMA; VARJEL classifications: C22; C32; E31; E37; E52

scholarly journals The Impact of Bank Credit on Inflation in Jordan by Using Vector Auto Regression Model: A Case Study of Jordan during 1968-2017

2019 ◽  
Vol 12 (5) ◽  
pp. 34
Author(s):  
Suleiman Daood Al-Oshaibat ◽  
Hmood H. Banikhalid
Keyword(s):  
Regression Model ◽  
Inflation Rate ◽  
Function Analysis ◽  
Explanatory Power ◽  
Mutual Effect ◽  
Bank Credit ◽  
Annual Data ◽  
Vector Auto Regression ◽  
The Impact ◽  
Auto Regression

Previous studied revealed mixed results regarding the Banks have an influence on the inflation rate. This study aims at investigating the impact of the bank credit on the inflation rate in Jordan during the period 1968-2017 by using Vector Auto Regression Model (VAR) on the annual data. Necessary tests were conducted for this model such as Unit Root Test, Granger Causality Test, Variance Decomposition and Response Function analysis. The results reveal that there is a mutual effect between the bank credit and the inflation rate. Moreover the study states that there is an explanatory power of the bank credit in explaining the changes in inflations rates in Jordan. Namely, there is a positive effect of the credit bank on the inflation rate in Jordan.

scholarly journals Military Expenditure and Macroeconomic Perfromance – The Case of an Emerging Country

2020 ◽  
Vol 65 (1) ◽  
pp. 67-83
Author(s):  
Patrick Ologbenla
Keyword(s):  
Exchange Rate ◽  
Inflation Rate ◽  
Foreign Currency ◽  
Military Expenditure ◽  
Emerging Country ◽  
Domestic Prices ◽  
Short Run ◽  
Vector Auto Regression ◽  
Exchange Rate Shocks ◽  
Auto Regression

AbstractThe study investigates the nexus between military expenditure and macroeconomic performance in Nigeria between 1980 and 2017. Data on military expenditure and some macroeconomic variables such as output (GDP), exchange rate and inflation rate are used in the study. The Vector Auto-regression technique VAR is applied so as to study the interactions among the variables in the short run. The result shows that military expenditure in Nigeria is significantly influenced by output and exchange rate shocks. It was also revealed that military expenditure does not make significant contributions to the behaviour of output in Nigeria. Military expenditure appears to be insulated against inflation shock since the largest chunk of military expenditure is traded in foreign currency hence less affected by domestic prices.

scholarly journals Non-Accelerating Inflation Rate Of Unemployment (NAIRU) In Iran

2011 ◽  
Vol 10 (11) ◽  
pp. 63
Author(s):  
Nahid Kalbasi ◽  
Maryam Ashtary
Keyword(s):  
Monetary Policy ◽  
World Economy ◽  
Inflation Rate ◽  
Recent Literature ◽  
Labor Law ◽  
Wage Rigidity ◽  
Var Model ◽  
Vector Auto Regression ◽  
Auto Regression ◽  
Structural Vector

The recent literature on monetary policy has raised many questions about the trade-off between inflation and unemployment and the assumption of a constant NAIRU. This paper tries to investigate the effects of monetary policy on NAIRU in Iran. We implement a structural Vector Auto Regression (VAR) model to measure the effects of monetary policy in shaping NAIRU in Irans economy. Our results suggest that monetary policy has negligible effects on NAIRU and the unemployment rate is mainly affected by labor market imperfections, such as wage rigidity, labor law, regulations, and institutions that do not match with todays world economy.

scholarly journals Minnesota—too late for a Sovereign Wealth Fund?

2021 ◽  
Author(s):  
Christopher R. McIntosh ◽  
Neil A. Wilmot ◽  
Adrienne Dinneen ◽  
Jason F. Shogren
Keyword(s):  
Renewable Resources ◽  
Iron Ore ◽  
Inflation Rate ◽  
Supply And Demand ◽  
Sovereign Wealth Funds ◽  
Funding Mechanism ◽  
Investment Return ◽  
Investment Returns ◽  
Fund Size ◽  
Forward Looking

AbstractTen states have created natural-resource-based Sovereign Wealth Funds (SWF) to allow a fraction of the wealth derived from the extraction of non-renewable resources to be available for future use. Minnesota does not have a SWF, even though companies have been mining in the state for over 100 years. Herein, we present backward and forward-looking scenarios to estimate the potential magnitude of a “what-if” extraction-based fund. A 1.5% of value tax is suggested as an SWF funding mechanism. Based on historical extraction, prices, and investment returns, a large SWF could already exist. In the forward-looking section, we begin by econometrically estimating the supply and demand of US iron ore production to better understand how an increase in mining taxes would likely effect mining output (i.e., the production effect). After accounting for an estimated 4% production loss, results suggest enough minerals could still be extracted to create a permanent fund with between $930 million (US) and $1.6 billion dollars (US) in direct contributions by 2050 (depending on price). Using reasonable assumptions of a 2% inflation rate and a 5% annual investment return, the fund size could range from $3 billion to $5 billion by 2050.

scholarly journals Movement of Inflation and New Keynesian Phillips Curve in ASEAN

Economies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 34
Author(s):  
Adhitya Wardhono ◽  
M. Abd. Nasir ◽  
Ciplis Gema Qori’ah ◽  
Yulia Indrawati
Keyword(s):  
Inflation Rate ◽  
Phillips Curve ◽  
New Keynesian ◽  
Inflation Expectations ◽  
New Keynesian Phillips Curve ◽  
Method Of Moment ◽  
Inflation Model ◽  
Wage Inflation ◽  
Generalized Method Of Moment ◽  
Forward Looking

The development of the theory of dynamic inflation begins by linking wage inflation and unemployment. In further developments, factor of expectation is classified into inflation model. The study used inflation data is important for ASEAN, because ASEAN is one of the strengths of the international economy. This study analyzes the dynamics of inflation in the ASEAN using framework the New-Keynesian Phillips Curve (NKPC) model. The data used is the quarterly panel data from 5 ASEAN members in the period 2005.QI–2018.QIV. The study of this dynamic inflation applies quarter to quarter inflation data, meaning that the inflation rate is the percentage change in the general price of the current quarter compared to last quarter general price divided by the last quarter. The empirical results are estimated by using the Generalized Method of Moment (GMM), both of the system and first different indicates that the pattern formation of inflation expectations are backward-looking and forward-looking. In addition, the estimated NKPC models show the backward-looking behavior is more dominant than the forward looking. Changes in inflation are not entirely influenced by expectations of inflation in each country. Changes in inflation are also influenced by the output gap, changes in money supply, and exchange rate. Based on the findings of this study, it can be concluded that the NKPC models can explain the dynamics of inflation in each country in the ASEAN region.

scholarly journals PERSISTENSI INFLASI DI JAKARTA DAN IMPLIKASINYA TERHADAP KEBIJAKAN PENGENDALIAN INFLASI DAERAH

2011 ◽  
Vol 14 (1) ◽  
pp. 5-30 ◽  
Author(s):  
Trinil Arimurti ◽  
Budi Trisnanto
Keyword(s):  
Empirical Result ◽  
Inflation Persistence ◽  
Inflation Expectation ◽  
High Inflation ◽  
High Level ◽  
Forward Looking

The main objective of this study is to measure the persistence of inflation level in Jakarta. In addition, this study intends to find out the source of inflation persistence and its implication to regional inflation control. The analysis of the regional inflation behavior developed in this paper is explored to commodities level. The empirical result indicates that the level of inflation persistence in Jakarta is relatively high, stemmed from high level of inflation persistance for most of commodities that construct inflation. Using the estimation results of the hybrid NKPC model, it shows that high inflation persistence in Jakarta mainly caused by inflation expectation, which is a combination of forward and backward looking. In this regards, it requires efforts gradually transform the behavior of inflation expectation to be more forward looking. Keywords: inflation peristence, expectation, NKPC.JEL Classification:E31, R10

scholarly journals Bitcoin Network Mechanics: Forecasting the BTC Closing Price Using Vector Auto-Regression Models Based on Endogenous and Exogenous Feature Variables

2020 ◽  
Vol 13 (9) ◽  
pp. 189 ◽  
Author(s):  
Ahmed Ibrahim ◽  
Rasha Kashef ◽  
Menglu Li ◽  
Esteban Valencia ◽  
Eric Huang
Keyword(s):  
Regression Models ◽  
Prediction Models ◽  
Vector Autoregression ◽  
State Of The Art ◽  
Bayesian Regression ◽  
Major Question ◽  
Factors Of Influence ◽  
Vector Auto Regression ◽  
Auto Regression ◽  
Price Discovery Process

The Bitcoin (BTC) market presents itself as a new unique medium currency, and it is often hailed as the “currency of the future”. Simulating the BTC market in the price discovery process presents a unique set of market mechanics. The supply of BTC is determined by the number of miners and available BTC and by scripting algorithms for blockchain hashing, while both speculators and investors determine demand. One major question then is to understand how BTC is valued and how different factors influence it. In this paper, the BTC market mechanics are broken down using vector autoregression (VAR) and Bayesian vector autoregression (BVAR) prediction models. The models proved to be very useful in simulating past BTC prices using a feature set of exogenous variables. The VAR model allows the analysis of individual factors of influence. This analysis contributes to an in-depth understanding of what drives BTC, and it can be useful to numerous stakeholders. This paper’s primary motivation is to capitalize on market movement and identify the significant price drivers, including stakeholders impacted, effects of time, as well as supply, demand, and other characteristics. The two VAR and BVAR models are compared with some state-of-the-art forecasting models over two time periods. Experimental results show that the vector-autoregression-based models achieved better performance compared to the traditional autoregression models and the Bayesian regression models.

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