Inflation Series Research Articles

Individuals Can be Taught to Sense the Degree of Vascular Occlusion: Implications for Practical Blood Flow Restriction.

Song, JS, Hammert, WB, Kataoka, R, Yamada, Y, Kang, A, and Loenneke, JP. Individuals can be taught to sense the degree of vascular occlusion: Implications for practical blood flow restriction. J Strength Cond Res 38(8): 1413-1418, 2024-It is currently unknown if individuals can be conditioned to a relative arterial occlusion pressure (AOP) and replicate that pressure at a later time point. The purpose of this study was to determine whether individuals can be taught to sense a certain relative pressure (i.e., target pressure) by comparing a conditioning method with a time-matched non-conditioning control. Fifty-eight subjects completed 2 visits in a randomized order: (a) conditioning condition and (b) time-matched control condition. The conditioning involved 11 series of inflations to 40% AOP for 12 seconds followed by cuff deflation for 22 seconds. The pressure estimations were taken at 5 and 30 minutes after each condition. Data are presented as mean differences (95% credible interval). The absolute error at 5 minutes was greater for the control compared with conditioning condition (7.1 [2.0-12.1] mm Hg). However, this difference in absolute error between conditioning and control was reduced at 30 minutes (2.9 [-1.3 to 7.1] mm Hg). The mean difference and 95% limits of agreement for the control were 8.2 (-42.4 to 58.5) mm Hg at 5 minutes and 0.02 (-43.5 to 43.5) at 30 minutes. The agreements for the conditioning were -6.2 (-32.4 to 20.0) mm Hg at 5 minutes and -11.2 (-36.6 to 14.3) mm Hg at 30 minutes. The results suggest that the individuals can be taught to sense the target pressure, but this effect only lasts a short amount of time. Future work is necessary to refine the conditioning method to extend the duration of this conditioning effect.

Forecasting Inflation with the New Keynesian Phillips Curve: Frequencies Matter*

AbstractWe forecast US inflation with a new Keynesian Phillips curve (NKPC) in the frequency domain. Our method consists of decomposing the time series of inflation and its NKPC predictors into several frequency bands, forecasting separately each frequency component of inflation, and then summing up those forecasts to obtain the forecast for aggregate inflation. We find that (i) accurately forecasting the low frequency of inflation is, on average, crucial to successfully forecast inflation; (ii) our NKPC low‐frequency forecast model consistently and significantly outperforms the time‐series NKPC and standard benchmark models; (iii) the low frequencies of inflation expectations and unemployment are the key predictors; and (iv) optimally switching on / off the forecasts of each frequency components of inflation at each period allows to outstandingly track inflation and show that all frequencies of inflation matter.

Inflation dynamics and persistence: The importance of the uncertainty channel

In this article, we employ a time-varying GARCH-type specification to model inflation and investigate the behaviour of its persistence. Specifically, by modelling the inflation series as AR(1)-APARCH(1,1)-in-mean-level process with breaks, we show that persistence is transmitted from the conditional variance to the conditional mean. Accordingly, we propose a new measure of time-varying persistence, which not only distinguishes between changes in the dynamics of inflation and its volatility but also allows for feedback between the two variables. Analysing the inflation series for a number of countries, we find evidence that inflation uncertainty plays an important role in shaping expectations, and a higher level of uncertainty increases inflation persistence. We also consider a number of unit root tests and present the results of a Monte Carlo experiment to investigate the size and power properties of these tests in the presence of breaks in the mean and the variance equation of an AR(1)-APARCH(1,1)-in-mean-level data generating process. The Monte Carlo experiment reveals that if the model is misspecified, then commonly used unit root tests will misclassify inflation as a nonstationary, rather than a stationary process.

The Relationship between Energy Inflation and Exchange Rate: A Study on Türkiye

Energy is among the indicators that are taken into consideration in increasing the production levels of countries and increasing their welfare. Energy has become an indispensable resource for the industrialization of countries, increasing their industrial production and ensuring their development and growth in this direction. Today, the development and growth of countries have become linked to their energy consumption. However, countries that lack energy resources need to import the energy resources they need in order to realize their development and growth, and their economic activities for this purpose are closely related to other economic indicators, especially the exchange rate, and bring about a series of economic results. This study examines the existence of the relationship between energy inflation and the real exchange rate in Türkiye in light of the fact that Türkiye is heavily dependent on foreign energy consumption. Accordingly, the study utilizes monthly series of energy inflation and real exchange rate variables for the period 2012:M01-2021:M12 for Türkiye. In the study, firstly, the series of the variables are seasonally adjusted with the help of a computer package program, then the variables are logarithmically transformed and the stationarity of the series of the variables is analyzed. According to the results of ADF and PP unit root tests, it is concluded that the series of energy inflation and real exchange rate variables are not stationary at level, but both series become stationary after first differences are taken. In the study, Engle-Granger cointegration analysis was conducted in accordance with the unit root test results. According to the results of cointegration analysis, energy inflation and real exchange rate variables are found to move together in the long run. Finally, Granger causality test analysis was conducted and according to the results of this analysis, the existence of bidirectional causality in the Granger sense between energy inflation and real exchange rate was determined.

Reconstruction of Large Periorbital Defect With a Pre-expanded Retrograde Postauricular Island Flap: Our 13-Year Experiences.

The clinical application of the retrograde postauricular island flap has been widely restricted because of its limited size and high morbidity of venous congestion. Thus, in this article, we introduced a pre-expanded retrograde postauricular island flap to reconstruct the large periorbital defect. A total of 13 patients with periorbital lesions who had undergone the treatment of our flap were enrolled in the study. The whole series of operations was divided into 3 parts, including expander implantation in the postauricular region, a series of expander inflations, and flap transferring, and special incisions were also designed in the procedure. In the end, all the flaps survived without serious complications. The mean size of the harvested flaps was 2.65 times larger than that of our nonexpanded cases. The reconstructed periorbital region showed a functional and aesthetic repair outcome after a follow-up of 3 to 30 months. To conclude, the pre-expanded retrograde postauricular island flap was a safe way to reconstruct a larger periorbital defect.

One-stop source: A global database of inflation

This paper introduces a global database that contains inflation series: (i) for a wide range of inflation measures (headline, food, energy, and core consumer price inflation; producer price inflation; and gross domestic product deflator changes); (ii) at multiple frequencies (monthly, quarterly and annual) for an extended period (1970–2023); and (iii) for a large number (up to 209) of countries. As it doubles the number of observations over the next-largest publicly available sources, the database constitutes a comprehensive, single source for inflation series. It also illustrates the potential use of the database with three applications. First, it studies the evolution of inflation since 1970 and documents the broad-based disinflation around the world over the past half-century, with global consumer price inflation down from a peak of 16.9 percent in 1974 to 2.5 percent in 2020, before rising to 7.8 percent in 2022. Second, the paper analyzes the role of common factors in explaining movements in different measures of inflation. While, across all inflation measures, inflation synchronization has risen since the early 2000s, it has been much higher for inflation measures that involve a larger share of tradable goods. In addition, the paper examines the behavior of inflation during global recessions. Global inflation fell sharply (on average by 0.9 percentage points) in the year to the trough of global recessions and continued to decline even as recoveries got underway.

Asymmetric Dynamics of Inflation Inertia in Some Selected Non-Eurozone European Countries

Relevance. Inflation inertia refers to the persistence of inflation over time and can be caused by a variety of factors, including expectations about future inflation, the structure of the economy, and the behavior of economic agents. Over the past two decades, the European economy has grappled with a range of challenges and currently seeks to mitigate the negative impacts of the global pandemic. Research objective. Persistent inflation can lead to uncertainty, decreased investment, and a loss of confidence in an economy. Non-eurozone economies can also face challenges in controlling inflation due to such factors as the lack of monetary integration with the eurozone, limited access to the European Central Bank's resources, and the lack of a unified currency. Hence, for a more effective monetary policy in these countries, it is necessary to measure and understand the inflation inertia. This paper offers a novel empirical study of the dynamics of inflation inertia for seven EU economies that are not part of the eurozone. Data and methods. To achieve the research objective, three non-linear unit root tests are employed to consider both structural changes and regime switching. These tests allowed for the inclusion of almost all non-linear dynamics observed in the inflation series. In addition, the tests involve the use of the dynamic rolling windows sample approach in order to provide more sensitive measurements of the effect of time-varying shocks on inflation inertia. Results. According to the static sample analysis of 200 observations, Bulgaria, Croatia, and the Czech Republic have inflation inertia. Sweden, Romania, Hungary, and Poland do not have inflation inertia when non-linear regime switching dynamics and structural change are considered. However, Croatia and the Czech Republic show a mostly non-stationary inflation in dynamic rolling windows sampling. Hungary has persistent inflation even though it was not detected in the static sample analysis. The shocks of inflation fade out in Bulgaria, Poland, Romania, and Sweden with non-linear dynamics. If non-linear dynamics is ignored, it can lead to misleading results in economic time series. Conclusions. Inflation inertia can be influenced by a variety of factors, including the global pandemic, global or regional conflicts and monetary policy preferences. The successful management of inflation inertia in Romania and Sweden may serve as a model for other economies that have demonstrated an ability to effectively address and mitigate the challenges posed by inflation inertia.

The gold price – Inflation relation in the case of Vietnam: empirical investigation in the presence of structural breaks

PurposeThis paper investigates the relationship between domestic gold prices and inflation in Vietnam based on the monthly series of the gold price index and consumer price index over the period of December 2001–July 2020.Design/methodology/approachThe co-integration between the domestic gold price and inflation is examined within the autoregressive distributed lag-error correction (ARDL bounds testing) framework. This paper also applies the vector error correction model (VECM) and impulse response function analysis to explore the causal relationship between these two variables. Moreover, since both gold and inflation series are likely to have structural changes over time, a unit root test controlling for significant breaks is employed in this paper.FindingsFindings from the ARDL bounds testing model suggest the presence of a co-integration between the underlying variables. The VECM indicates that shocks in inflation lead to a negative response to gold prices in the long run. In the short term, only fluctuations in gold prices impact inflation, and this causality is unidirectional.Research limitations/implicationsGold is regarded as a critical financial asset to preserve wealth from inflation pressure in the case of Vietnam. These findings propose implications for both investors and policymakers.Originality/valueEmpirical results suggest that inflation has a long-term impact on gold prices in the Vietnamese market. In the existence of a permanent inflationary shock, domestic prices of gold respond negatively to this shock; hence, gold can act as a good hedge against inflation in Vietnam.

THE INFLUENCE OF MONETARY POLICY ON HOUSING MARKET: EVIDENCES FROM TURKEY

Purpose: Nowadays, the changes in the level of economic activities in the housing market are accepted as the most important signal of macroeconomic performance. This situation brings about the need to give importance to the investigation of policy implementations that affect economic activity in the housing market. So, this study aims to find out the effects of changes in the monetary policy on housing prices in Turkey as a sample of developing country. Design/methodology/approach: This study employed Augmented Vector Autoregression (VAR) analysis. For housing prices; the Housing Unit price series, calculated by the Central Bank, spanning 2010M1-2016M3 are used. Housing unit price is calculated by Housing price per square meter. To represent production volume, the index of total industrial production has been used. To represent inflation series, CPU (Consumer Price Index) series have been used. The data has been taken from CBRT (the Central Bank of the Republic of Turkey) and TUIK (Turkish Statistical Institute). Findings: Results show that policy interest rates are important indicators for the related term?s housing prices and it can also be said that the housing price channel has partially been effective. Accordingly, results determined that monetary policy had a significant effect on housing prices in Turkish housing market. Originality/value: This study supports the argument that monetary policy has a significant effect on housing prices in developing countries like Turkey.

A study of inflation persistence in Kazakhstan: what has changed?

ABSTRACT The paper analyzes the persistence properties of the monthly inflation and its components in Kazakhstan using a fractionally integrated approach. The results suggest the presence of long memory behaviour in the inflation series. The general inflation, food inflation, and non-food inflation experienced a break in late 2015 when the National Bank of Kazakhstan announced a shift in the monetary policy regime. Non-food inflation is fractionally cointegrated with the nominal depreciation rate. The estimates of the Bayesian DSGE model reveal shifts in the sources of inflation persistence. The evidence for the effect of the policy change on inflation persistence and its sources is mixed. Finally, the estimation of the persistence parameter is sensitive to the choice of data frequency.

Forecasting Inflation, Exchange Rate, and GDP using ANN and ARIMA Models: Evidence from Pakistan

Purpose: The purpose of this study is to specify an efficient forecast model for the accurate prediction of macroeconomic variables in the context of Pakistan.
 Design/Methodology/Approach: We particularly investigate the comparative accuracy of Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) models-based predictions using monthly data of inflation, exchange rate, and GDP from 1990 to 2014.
 Findings: According to our findings, the ANN-based forecasted inflation series is more precise as compared to ARIMA-based estimates. On the contrary, the ARIMA model outperforms the ANN model for exchange rate forecasts with the forecasted values being very close to the actual values. Further, ARIMA performs comparatively better in forecasting GDP with relatively smaller forecast error. On the whole, our findings suggest the ARIMA model provides appropriate results for forecasting exchange rates and GDP, while the ANN model offers precise estimates of inflation.
 Implications/Originality/Value: Our findings have important implications for the analysts and policymakers highlighting the need to use appropriate forecasting models that are well aligned with the structure of an economy.

Investigating the periodicities of the Turkish food inflation with considering the subgroups

This paper empirically identifies the hidden periodicities in the time series of monthly food inflation of Turkey with its subgroups for the periods from January, 2004 to June, 2020. Periodicity is the hidden cycles of the time series which is beyond the seasonality. In order to deal with this hidden cycles periodogram based time series analysis is used. Also, future inflation ratios are forecasted by Harmonic regression. The results of this study reveal that food inflation of Turkey has cycles of approximately 2 years which is mostly derived by food and non-alcoholic beverage inflation.

Equilibrium indeterminacy and sunspot tales

We argue that dynamic indeterminacy in structural models can help rationalize statistical regularities regarding higher-order properties of macroeconomic time series. Without departing from the Gaussian rational expectations paradigm, we formally establish that any indeterminate equilibrium model admits a linear recursion with multiplicative noise representation. This allows self-fulfilling expectations (sunspots) to enhance endogenous propagation forces that trigger high-probability extreme changes in model variables, while also inducing time variation in conditional volatilities. As a result, even modest, short-lived exogenous shocks can produce large and persistent macroeconomic effects. Using a workhorse New Keynesian framework, we investigate the ability of such a general mechanism to account for observed fat-tailed behavior and volatility clusters in the inflation series over the Great Inflation period of US macroeconomic history.

Can Individuals Be Taught to Sense the Degree of Vascular Occlusion? A Comparison of Methods and Implications for Practical Blood Flow Restriction.

Bell, ZW, Spitz, RW, Wong, V, Yamada, Y, Song, JS, Abe, T, and Loenneke, JP. Can individuals be taught to sense the degree of vascular occlusion? A comparison of methods and implications for practical blood flow restriction. J Strength Cond Res 36(12): 3359-3365, 2022-The study objective was to determine whether subjects could be conditioned to a relative blood flow restriction pressure in the lower body and compare 2 separate conditioning methods (unconstrained vs. constrained). Thirty-five subjects completed 4 visits, involving measurements for arterial occlusion and pressure estimations at 5 minutes and 24 hours after conditioning. The constrained method involved applying 40% of measured arterial occlusion 11 times, along with 10% above and below this pressure. The unconstrained method was time-matched, involving a series of inflations to 40% arterial occlusion for 12 seconds and then deflated for 22 seconds. Data are presented as mean differences (95% credible interval) unless otherwise noted. The absolute error between conditioning methods was found to be similar at 5 minutes (-1.1 [-5.9, 3.7] mm Hg) and 24 hours (-2.4 [-7, 2.2] mm Hg) after conditioning. The constant error differed between methods at 5 minutes [-8.2 (-14.4, -1.9) mm Hg] but was similar at 24 hours (-2.5 [-8.5, 3.6] mm Hg; H0: 0.680; H1: 0.068; and H2: 0.252) after conditioning. The bias and 95% limits of agreement for the unconstrained method were -3.9 (-33.8, 25.9) mm Hg at 5 minutes and -2.9 (-32, 26.1) mm Hg at 24 hours. The agreement for the constrained method was 4.2 (-28, 36.5) mm Hg at 5 minutes and -0.54 (-37.3, 36.2) mm Hg at 24 hours. Conditioning methods produced similar levels of absolute error, indicating that either method may offer a viable means of pressure application. Most estimates were between 20 and 60% of arterial occlusion pressure. Additional conditioning sessions may be needed to narrow this range at the individual level.

Comparing Conditioning Methods: Implications For Practical Blood Flow Restriction Exercise

Previous research has shown that conditioning individuals to a relative pressure, surrounded by pressures too high and too low, may provide a suitable means for pressure application among practical blood flow restriction users. However, it is unknown if applying only the target pressure repeatedly would be as effective, compared to using a range of pressures. PURPOSE: To compare two separate conditioning methods (target pressure only vs. range of pressures) in the ability to estimate the target restriction pressure. METHODS: 35 participants (20 M, 15 F) were tested over 4 lab visits, involving measurements for arterial occlusion, and pressure estimations at 5-minutes and 24-hours following two separate conditioning methods. Participants arrived to the lab and proceeded to lie supine for a 10-minute rest period. The constrained method involved applying 40% of predetermined arterial occlusion, along with 10% above and below this pressure. The unconstrained method was time-matched, and involved a series of inflations to 40% arterial occlusion for 12 seconds, and then deflated for 22 seconds. Differences were assessed using BAIN. Three plausible hypotheses (H0, H1, and H2) were compared: e.g. H0 indicates the null hypothesis; H1 indicates the mean of variable 1 is bigger than the mean of variable 2; and, H2 indicates the mean of variable 1 is smaller than the mean of variable 2. Specific hypotheses were evaluated by comparing posterior probabilities. Data is presented as mean differences (95% credible interval). RESULTS: The absolute error between methods (unconstrained and constrained) was found to be similar at 5-minutes [-1.1 (5.9, 3.7) mmHg; H0: 0.728; H1: 0.089; H2: 0.183] and 24-hours [-2.4 (-7, 2.2) mmHg; H0: 0.634; H1: 0.056; H2: 0.310] post. The constant error between methods was found to differ at 5-minutes [-8.2 (-14.4, -1.9) mmHg; H0: 0.101; H1: 0.005; H2: 0.894] but was similar at 24-hours [-2.5 (-8.5, 3.6) mmHg; H0: 0.680; H1: 0.068; H2: 0.252] post. CONCLUSIONS: Each conditioning method produced similar levels of absolute error, indicating that either may be a viable method of pressure application. Studies implementing practical blood flow restriction have the option to utilize either conditioning method to estimate a relative pressure, around 40% of the resting arterial occlusion pressure.

Structural Breaks in U.S. Macroeconomic Time Series: A Bayesian Model Averaging Approach

AbstractWe investigate the evidence for structural breaks in autoregressive models of U.S. macroeconomic time series. There is substantial model uncertainty associated with such models, including uncertainty related to lag selection, the number of structural breaks, and the specific parameters that break. We develop a feasible approach to Bayesian model averaging, where the model space encompasses these sources of uncertainty. We find pervasive evidence for breaks in variance parameters, and for price inflation series, we find strong evidence of changes in persistence. We also find evidence for reductions in trend growth rates of production series. For most series, there is substantial model uncertainty, calling into question the common practice of basing inference on one selected structural break model.

One-Stop Source: A Global Database of Inflation

This paper introduces a global database that contains inflation series: (i) for a wide range of inflation measures (headline, food, energy, and core consumer price inflation; producer price inflation; and gross domestic product deflator changes); (ii) at multiple frequencies (monthly, quarterly and annual) for an extended time period (1970-2021); and (iii) for a large number of (up to 196) countries. As it doubles the number of observations over the next-largest publicly available sources, our database constitutes a comprehensive, single source for inflation series. We illustrate the potential use of the database with three applications. First, we study the evolution of inflation since 1970 and document the broad-based disinflation around the world over the past half-century, with global consumer price inflation down from a peak of roughly 17 percent in 1974 to 2.5 percent in 2020. Second, we examine the behavior of inflation during global recessions. Global inflation fell sharply (on average by 0.9 percentage points) in the year to the trough of global recessions and continued to decline even as recoveries got underway. In 2020, inflation declined less, and more briefly, than in any of the previous four global recessions over the past 50 years. Third, we analyze the role of common factors in explaining movements in different measures of inflation. While, across all inflation measures, inflation synchronization has risen since the early 2000s, it has been much higher for inflation measures that involve a larger share of tradable goods.

Using Models of the GARCH Family to Estimate the Level of Food and Non-Food Inflation in Ethiopia

An increase in inflation volatility implies higher uncertainty about future prices. As a result, producers and consumers can be affected by the increased inflation volatility, because it increases the uncertainty and the risk in the market. Thus, inflation volatility attracts the attention of researchers to find a suitable model which can predict the future conditions of the market. This study aims to fit appropriate ARMA-GARCH family models for food and non-food inflation rate of from the period January 1971 through June 2020. Since the main objective of the study is identifying an appropriate model for inflation series, the null and alternative hypotheses are defined in comparison of the two types of models. H0: The symmetric GARCH models better capture inflation volatility of Ethiopia. H1: The asymmetric GARCH models better capture inflation volatility of Ethiopia. The ARMA-GARCH family models were applied to capture the stylized facts of financial time series such us leptokurtic, volatility clustering and leverage effects. The mean model results show that, an ARMA (1, 2) and ARIMA (0, 1, 1) models are identified as the best fitted model for food and non-food inflation, respectively. From the estimation results of volatility model, an asymmetric TGARCH (1, 1) model with Student's t- distributional assumptions of the residual is the best model for non-food inflation. Thus, modeling of information, news of events is very significant determinants of volatility and GARCH family models are appropriate for the given series (monthly food-inflation volatility) of Ethiopia under the study period considered.

Long-memory modeling and forecasting: evidence from the U.S. historical series of inflation

Abstract We report the results of applying several long-memory models to the historical monthly U.S. inflation rate series and analyze their out-of-sample forecasting performance over different horizons. We find that the time-varying approach to estimating inflation persistence outperforms the models that assume a constant long-memory process. In addition, we examine the link between inflation persistence and exchange rate regimes. Our results support the hypothesis that floating exchange rates associate with increased inflation persistence. This finding, however, is less pronounced during the era of the Great Moderation and the Federal Reserve System’s commitment to inflation targeting.

The Relationship between Inflation and Interest Rates in the UK: The Nonlinear ARDL Approach

Abstract This study reconsiders the Fisher effect for the UK from a different methodological perspective. To this aim, the nonlinear ARDL model recently developed by Shin et al. (2014), is applied over the periods of 1995M1-2008M9 and 2008M10-2018M1. This model decomposes the changes in original inflation series as two new series: increases and decreases in inflation rates. Hence, it enables us to examine the Fisher effect in terms of increases and decreases in inflation separately. The empirical findings support asymmetrically partial Fisher effects for the UK in the long-run only for the first period. Additionally, this study attempts to describe and introduce a different version of the partial effect concept for the first time for the UK.