CPI Inflation Research Articles

Do global output gaps help forecast domestic inflation? Evidence from Phillips curves for Poland

This study confronts domestic and global views on inflation through the use of the Hybrid New Keynesian Phillips Curve (HNKPC) models estimated for headline and core inflation in Poland. We analyse the roles of the global vs. domestic output gaps in affecting price changes. We ensure that our conclusions are robust by taking into consideration various proxies for inflation expectations, imported inflation, the domestic output gap and the global output gap.Our results suggest that the global demand conditions are statistically insignificant in the majority of the estimated global versions of HNKPC, independently of the measure of them that is considered. In terms of empirical fit, and especially of the out-of-sample forecasting accuracy, the specifications of the Phillips curve with the domestic and global output gaps among the explanatory variables are not superior to traditional Phillips curves. Interestingly, the relative importance of the global output gap is much smaller in models that are estimated in terms of core inflation, excluding foodstuffs and energy, than in CPI inflation models. This suggests that global demand conditions affect the inflation in Poland indirectly, mainly through the prices of food and energy raw materials.The main conclusion from our study is that external factors that are already considered in the traditional hybrid versions of the new Keynesian Phillips curve are sufficient to account for global influences on prices in the domestic economy. The concept of the global output gap improves neither the explanatory nor the predictive power of HNKPC models.

The paradox of rising wage growth and falling inflation

▀ Strong labour markets and rising wages in advanced economies stand in sharp contrast to recent declines in economists’ inflation forecasts and market expectations. In our view, though, these developments are not necessarily contradictory. Even if wage growth edges higher, we think demand factors will limit any pick‐up in prices. Instead, we expect firms’ margins will be squeezed. ▀ Although the labour share has risen more sharply than we had expected over the past couple of years, we are sceptical that this will translate into substantially stronger underlying inflation. Not only has the rise been small, it has been employment rather than wages that has surprised to the upside. The strength of employment is probably more about firms’ production preferences than workers’ capitalising on a stronger negotiating position. ▀ True, wages adjusted for productivity now look high by historical standards. But neither theory or empirical evidence suggests that this must inevitably lead to stronger CPI inflation in the short‐term. Our forecast for flat wage growth in 2019 and the absence of strong cost pressures elsewhere are also a comfort. ▀ Inflation tends to be more responsive to demand indicators – and the recent GDP growth soft patch suggests any further pick‐up in underlying inflation pressures will be limited (see Chart below). ▀ More generally, we think that the consensus view on inflation for the key advanced economies is high. Market‐based inflation expectations are typically lower than our own, which may reflect the perception that inflation risks are skewed to the downside. Positive economic surprises could lead downside risks to narrow, but ageing expansions and secular stagnation worries suggest this is unlikely, limiting any future pick‐up in bond yields.

Forecasting using supervised factor models

This paper examines the theoretical and empirical properties of a supervised factor model based on combining forecasts using principal components (CFPC), in comparison with two other supervised factor models (partial least squares regression, PLS, and principal covariate regression, PCovR) and with the unsupervised principal component regression, PCR. The supervision refers to training the predictors for a variable to forecast. We compare the performance of the three supervised factor models and the unsupervised factor model in forecasting of U.S. CPI inflation. The main finding is that the predictive ability of the supervised factor models is much better than the unsupervised factor model. The computation of the factors can be doubly supervised together with variable selection, which can further improve the forecasting performance of the supervised factor models. Among the three supervised factor models, the CFPC best performs and is also most stable. While PCovR also performs well and is stable, the performance of PLS is less stable over different out-of-sample forecasting periods. The effect of supervision gets even larger as forecast horizon increases. Supervision helps to reduce the number of factors and lags needed in modelling economic structure, achieving more parsimony.

Forecasting Inflation in Russia Using Dynamic Model Averaging

In this study, I forecast CPI inflation in Russia using the method of Dynamic Model Averaging pseudo out-of-sample on historical data. This method can be viewed as an extension of Bayesian Model Averaging, where the identity of the model that generates data is allowed to change over time, as are the model parameters. DMA is shown not to produce forecasts superior to simpler benchmarks, even if a subset of individual predictors is pre-selected ‘with the benefit of hindsight’ from the full sample. The two groups of predictors that give the highest average values for the posterior inclusion probability are loans to non-financial firms and individuals, along with actual and anticipated wages.

The UK Economy

The UK's future relationship with the European Union (EU) remains undecided even though the Article 50 exit date is less than two months away. Brexit uncertainty has intensified since our last forecast and is now evident in various indicators.Our main forecast is conditional on a ‘soft’ Brexit scenario. Under this scenario, GDP growth stabilises at around 1.5 per cent this year before recovering to 1.7 per cent in 2020. CPI inflation eases to the target level of 2 per cent over this period.We expect the Bank of England to raise Bank Rate by 25 basis points in August. We also expect the Chancellor to spend more than the latest OBR forecast. That, together with the reclassification of student loans in public deficit data, will mean that the Chancellor is set to breach the fiscal mandate.There is a chance that the UK exits the EU without a deal at the end of March. Policymakers will have more room to inject stimulus if inflation expectations remain anchored.

Forecasting the UK economy with a medium-scale Bayesian VAR

We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP growth and CPI inflation in real time relative to forecasts from COMPASS, the Bank of England’s DSGE model, and other benchmarks. We find that the BVAR outperformed COMPASS when forecasting both GDP and its expenditure components. In contrast, their performances when forecasting CPI were similar. We also find that the BVAR density forecasts outperformed those of COMPASS, despite under-predicting inflation at most forecast horizons. Both models over-predicted GDP growth at all forecast horizons, but the issue was less pronounced in the BVAR. The BVAR’s point and density forecast performances are also comparable to those of a Bank of England in-house statistical suite for both GDP and CPI inflation, as well as to the official Inflation Report projections. Our results are broadly consistent with the findings of similar studies for other advanced economies.

Inflation Dynamics: Dead, Dormant, or Determined Abroad?

Inflation dynamics have been difficult to explain over the last decade. This paper explores whether a more comprehensive treatment of globalization can help. CPI inflation has become more synchronized around the world since the 2008 crisis, but core and wage inflation have become less synchronized. Global factors (including commodity prices, world slack, exchange rates, and global value chains) are significant drivers of CPI inflation in a cross-section of countries, and their role has increased over the last decade, particularly the role of nonfuel commodity prices. These global factors, however, do less to improve our understanding of core and wage inflation. Key results are robust to using a less-structured trend-cycle decomposition instead of a Phillips curve framework, with the set of global variables more important for understanding the cyclical component of inflation over the last decade but not the underlying slow-moving inflation trend. Domestic slack still plays a role for all the inflation measures, although globalization has caused some "flattening" of this relationship, especially for CPI inflation. Although CPI inflation is increasingly determined abroad, core and wage inflation are still largely domestic processes.

An evaluation of the forecast performance of DSGE and VAR Models: The case of a developing country

This paper estimates a DSGE model and three versions of VAR models (VARX, BVARX and BVAR) to analyze forecasting performance of these models in context of Pakistan. VAR models and a medium-scale DSGE model are estimated using quarterly data (1980Q4-2017Q2). Expanding window recursive out-of-sample forecasts for GDP growth, call money rate, CPI inflation and percent change in exchange rate are generated and compared over the period 2009Q1-2017Q2. Forecasting performance is analyzed by the comparison of bias and root mean squared errors (RMSE). Analysis of forecasting performance over 1-8 quarters forecast horizon reveals that BVAR model provides relatively better forecast in case of GDP growth, interest rate and inflation while BVARX provides more accurate forecast in case of exchange rate. In case of GDP growth, inflation and exchange rate, forecasting performance of DSGE model considerably improves as forecasting horizon expands. For longer forecast horizons, divergence between DSGE and Bayesian VAR forecasts tends to disappear. This implies that DSGE model is more relevant for medium term forecasting rather than short term forecasting. Structural interpretation of DSGE forecast errors reveals that there has been unutilized growth potential in economic activity. This slack in economic activity might be attributable to unnecessarily high interest rate and overvalued exchange rate.

Comment on “Indian Monetary Policy in the Time of Inflation Targeting and Demonetization”

Comment on “Indian Monetary Policy in the Time of Inflation Targeting and Demonetization”

Exchange Rate Pass-Through, Nominal Wage Rigidities, and Monetary Policy in a Small Open Economy

This paper discusses the design of monetary policy in a New Keynesian small open economy framework by introducing nominal wage rigidities and incomplete exchange rate pass-through on import prices. Three main findings are summarized. First, with the existence of an incomplete exchange rate pass-through and nominal wage rigidities, the optimal policy is to seek to minimize the output gap, the variance of domestic price and wage inflation, as well as deviations from the law of one price. Second, the CPI inflation targeting Taylor rule is welfare enhancing when there is a technological shock to the economy. The exception occurs when there is a foreign income shock, which minimizes welfare losses under the domestic inflation targeting Taylor rule. Last, two stylized Taylor rules turn out to be a bad approximation, but the modified Taylor rules that respond to the unemployment gap rather than the output gap are a closer approximation to the optimal policy.

On the reduced macroeconomic volatility of the Australian economy: Good policy or good luck?

The Australian economy has experienced various changes in macroeconomic conditions over the past four decades. These changes have been associated with reduced volatility in key macroeconomic variables: CPI inflation, real GDP and the TWI measured real exchange rate. In light of this fact, my objective in this paper is to determine whether this reduction is associated with good policy or good luck. To this end, I estimate a time varying structural VAR model that is identified with theoretically consistent sign restrictions from a small open economy dynamic stochastic general equilibrium model. The primary result is that both non-systematic and systematic monetary policy have changed over the past four decades. In particular, non-systematic responses of inflation, real GDP and the exchange rate have increased since the adoption of a flexible exchange rate in 1983, while systematic responses of the cash rate to inflation have experienced various changes in intensities, exhibiting a trend towards a more passive behaviour since the 2007/08 financial crisis. Taken together, these results suggest that the reduction in macroeconomic volatility is associated with good policy.

Dismiss the output gaps? To use with caution given their limitations

The link between inflation and the output gap is central to the conduct of monetary policy. In this paper, we use a new real-time database for Canada to study various output gap measures. We analyze output gap revisions and assess the usefulness of these gaps in forecasting total CPI inflation and three newly developed measures of core CPI inflation: CPI-median, CPI-trim and CPI-common. We also consider labour input gaps, projected output gaps, and simple combinations of output gaps. We find that, when forecasting CPI-common and CPI-trim, some gaps appear to provide information that reduces forecast errors when compared with models that use only lags of inflation. However, forecast improvements are rarely statistically significant. In addition, we find little evidence of the usefulness of output gaps in forecasting inflation measured by total CPI and CPI-median. These results call for cautiousness when central banks use output gaps to forecast inflation as their usefulness is limited.

Downward nominal wage rigidity in Canada: Evidence from micro‐level data

AbstractWe assess the importance of downward nominal wage rigidity (DNWR) in Canada using employer‐level administrative data from the major wage settlements (MWS) and household‐based survey data from the Survey of Labour Income Dynamics (SLID). MWS data cover large unionized firms in Canada, while SLID is a rich rotating panel representative of the employed population in Canada. Combining both sources of information allows for an extensive analysis of DNWR in the Canadian labour market. We find large shares of wage freezes and smaller shares of wage cuts in both MWS and SLID. Shares of freezes are higher at lower CPI inflation rates, based on provincial data. These observations are consistent with the presence of DNWR. DNWR in Canada appears to be larger than in other countries such as the United States, the United Kingdom and European countries. The incidence of DNWR is heterogeneous across firms’ and workers’ characteristics. Wages report less DNWR over longer horizons.

House-Prices and the Credit Market - Evidence from an International Panel of Industrialized Economies

In this article, we analyze to what extent the influence of housing market determinants and especially the credit market vary across countries and time. We do this by means of an international panel data set, consisting of quarterly data for 18 industrialized countries between 1975/01 and 2017/02. Moreover, we test whether our findings hold true when controlling for periods of house-price booms and busts relative to normal phases, a structural break in 1985 (Great Moderation), as well as selected characteristics of housing finance. Five results are worth highlighting. First, house-prices are best explained by disposable income, residential investment, the unemployment rate, the credit market, a business cycle dummy, and the cpi inflation. Second, the cpi inflation and the business cycle dummy are only significant after 1985, but are insignificant before. Third, the credit market only influences house-prices in normal and boom times, and the cpi inflation only in normal and bust times. Fourth, the LTV ratio has a strong and positive impact on house-price growth, and fifth, the degree to which an increase in credit growth is passed on to the housing market is strongest in countries with high LTV ratios in normal times, and in countries with more developed secondary mortgage markets in boom times.

R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability

ABSTRACTA long-standing puzzle in macroeconomic forecasting has been that a wide variety of multivariate models have struggled to out-predict univariate models consistently. We seek an explanation for this puzzle in terms of population properties. We derive bounds for the predictive R2 of the true, but unknown, multivariate model from univariate ARMA parameters alone. These bounds can be quite tight, implying little forecasting gain even if we knew the true multivariate model. We illustrate using CPI inflation data. Supplementary materials for this article are available online.

Internet Rising, Prices Falling: Measuring Inflation in a World of E-Commerce

The rise of ecommerce and the contrasts between online and traditional retail pricing behavior have raised questions about potential bias in CPI inflation. Using new data on online transactions, this paper shows that aggregate matched-model inflation online from 2014-2017 was more than a full percentage point lower than in the corresponding CPI. In addition, new products were tremendously important. Quantifying the net increase in number of new goods minus the exit of old goods suggests that actual inflation online may have been an additional 1.5 to 2.5 percentage points lower than indicated in matched model price indices like the CPI.

Measures of Inflation in India

This paper brings out the salient features of different measures of inflation in India. Before adopting the flexible inflation targeting framework, RBI focused on using Wholesale Price Index (WPI) as the measure of headline inflation. Consumer Price Index for Industrial Workers (CPI-IW) was the widely used measure of CPI inflation. International practice however, suggests the use of CPI as the measure of headline inflation. There are also limitations of using WPI as a measure of inflation. Hence, Central Statistics Office (CSO), launched a new measure of CPI, known as CPI-Combined which incorporates all Indian rural and urban households. Stylized facts used in the paper show that inflation dynamics in India is characterised by a divergence between CPI-IW and WPI indices. Against this backdrop, the paper examines Granger Causality between the two indices in a Vector Auto Regressive framework. Results of the study indicate that there is bidirectional causality between the two indices which does not get affected even during the period of global financial crisis, when the divergence between the two indices was observed for the longest duration.

Do inflation expectations granger cause inflation?

In this paper, we investigate whether survey measures of inflation expectations in Sweden Granger cause Swedish CPI inflation. This is done by studying the precision of out-of-sample forecasts from Bayesian VAR models using a sample of quarterly data from 1996 to 2016. It is found that the inclusion of inflation expectations in the models tends to improve forecast precision. However, the improvement is typically small enough that it could be described as economically irrelevant. One exception can possibly be found in the expectations of businesses in the National Institute of Economic Research’s Economic Tendency Survey; when included in the models, these improve forecast precision in a meaningful way at short horizons. Taken together, it seems that the inflation expectations studied here do not provide a silver bullet for those who try to improve VAR-based forecasts of Swedish inflation. The largest benefits from using these survey expectations may instead perhaps be found among analysts and policy makers; they can after all provide relevant information concerning, for example, the credibility of the inflation target or challenges that the central bank might face when conducting monetary policy.

UK inflation set to tumble below target by autumn

▀ We expect CPI inflation to slow markedly this year, dropping below the 2% target by the autumn. The inflationary impulse from the 2016 depreciation is fading and should partially reverse, while global food and energy prices are expected to stabilise. Base effects will become increasingly important. ▀ CPI inflation reached a five‐and‐a‐half‐year high of 3.1% in November, up from a little over 1% a year earlier. The 2017 pick‐up in inflation was the result of a perfect storm of a weaker pound, higher oil prices and sharp rises in domestic electricity bills. But inflation has subsequently slowed, reaching 2.5% in March. And, after a brief hiatus, we expect the downward trend to continue as we move through the year. ▀ The key driver of lower inflation will be weaker core pressures. In line with the literature, there is already evidence that the impact of sterling's depreciation is fading, and we think that the pressures could partially reverse if sterling continues to strengthen. We see little prospect of an offsetting escalation in domestic cost pressures. The recent pick‐up in wage growth has been muted and a further acceleration above 3% looks unlikely while there remains slack in the labour market. ▀ The food, petrol and energy categories contributed 0.8 ppt to CPI inflation last year, compared with a drag of 0.5 ppt in 2016, as stronger global pressures combined with the weaker pound. But as global prices have been more subdued of late, by the end of 2018, we expect these categories to be contributing 0.5 ppt to CPI inflation. ▀ The final element behind the expected slowdown in inflation is base effects. The comparison with last year's strong price pressures will depress the 2018 inflation rate, and we see the base effects being at their strongest mid‐year. ▀ We think it unlikely that such a slowdown in inflation would derail the MPC from hiking interest rates twice this year. But it could temper its hawkishness in 2019.

Analyzing inflation in Nigeria: a fractionally integrated ARFIMA-GARCH modelling approach

The study looked into the stochastic properties of CPI-inflation rate for Nigeria from 1995Q1 to 2016Q4. The study employed an autoregressive fractionally integrated moving average and a general autoregressive conditional heteroskedasticity (ARFIMA-GARCH) methodology as well as ADF/KPSS to investigate the long-memory properties of CPI-Inflation for Nigeria. The study found that CPI-inflation in Nigeria is shock dissipating at a geometric rate (fast mean reverting ability). The ARFIMA-GARCH process showed that CPI inflation in Nigeria is a heteroskedastic fractionally integrated process with quick mean reverting ability. The study therefore concludes that shocks to CPI-inflation in Nigeria such as sudden hikes in prices of energy products will not cause a permanent change in general price level but will eventually return to its mean state, and therefore having an implication for the Inflation-Unemployment tradeoff of the Philips curve.