A Markov-Switching Model of Inflation in Bolivia

Bojanic, Antonio N.

doi:10.3390/economies9010037

Cited by 11 publications

(7 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The most recent literature on the quantity equation and inflation uses Markov switching models to describe inflation. Bojanic (2021) analyzed the Bolivian inflation process by utilizing a time-varying univariate and multivariate Markov switching model, and found that the results generally fall in line with what the quantity theory of money predicts. He further found that by partitioning the sources of inflation, he can demonstrate that, from a long-term perspective and in a high-inflation regime, differences in inflation are mostly explained by GDP growth.…”

Section: Introductionmentioning

confidence: 72%

See 1 more Smart Citation

Predicting Inflation—A Holistic Approach

Avdiu

Unger

2022

JRFM

View full text Add to dashboard Cite

The quantity equation is a well-established, theoretic, long-run concept that has been criticized for a variety of reasons, i.e., that no precise statements about causality or dynamics between money growth and inflation can be inferred from its components. These shortcomings can be tackled by estimating inflation based upon a holistic approach and the performance of a ceteris paribus analysis for various levels of quantity and velocity of money, as well as GDP. By testing the validity of the quantity equation, it is possible to evaluate possible effects of elevated budget deficits, unprecedented expansions of the monetary base caused by global lockdowns, and a crash in global productivity, on inflation. The main findings of this paper suggest that the level of productivity is the main driver of inflation. The quantity and velocity of money only play a subordinate role in the determination of the inflation level. If inflation is holistically seen as a function of the quantity and velocity of money, as well as general economic productivity, the level of inflation can be very well explained by comparing the supply side with general economic productivity.

show abstract

Section: Introductionmentioning

confidence: 72%

“…This finding is in line with our findings. However, in contrast to Bojanic (2021), we further determine the relative explanatory contribution of GDP growth to money and velocity by estimating the parameters holistically.…”

Section: Introductionmentioning

confidence: 99%

Predicting Inflation—A Holistic Approach

Avdiu

Unger

2022

JRFM

View full text Add to dashboard Cite

show abstract

Section: The Results and Discussionmentioning

confidence: 99%

“…We estimated the short-term interest rate by including only the constant as the explanatory variable. The regimes are generally identified according to the estimated constant terms, the standard deviations or transition probabilities (Bojanic, 2021). Results of our estimations presented in Table 2 revealed that the constant term of regime 1 (0.041) is inferior to that of regime 2 (0.070).…”

Section: Identification and Characterization Of Regimesmentioning

confidence: 86%

Financial stability and monetary policy of the Central Bank of West African Countries: a Markov-Switching model

Houngbédji

Bassongui

2022

JES

View full text Add to dashboard Cite

Purpose This paper aims to examine the response of monetary policy to financial instability in the West African Economic and Monetary Union.Design/methodology/approach Through annual aggregated data from 1970 to 2019, the empirical strategy is based on the Markov regime-switching model with fixed probabilities.Findings The results revealed that the monetary policy of the central bank of the West African Economic and Monetary Union is characterized by two regimes (calm and distress) with respect to the trend of financial stability. The authors also found that the occurrence of the calm regime was likely greater than that of the distress regime. In addition, the calm regime is longer than the distress regime. The authors finally revealed that the central bank reacts to financial instability risk by increasing its short-term interest rate when financial instability reaches a threshold.Research limitations/implications The limitation of this study is the unavailability of monthly or quarterly data that are more suitable for the methodological approach adopted.Originality/value This study is the one to estimate the response of the Central Bank of West African Countries to financial stress using a novel approach based on the Markov-Switching regression.

show abstract

“…Besides, individual markets experience varying predictability levels attributable to market conditions (Urquhart and McGroarty 2016) and hence, nonlinear modelling of the market dynamics is required to ascertain accurate conclusions about the behavior of economic variables, such as the performance of fund portfolios. Bojanic (2021) explained that Markov switching models are mostly employed for the analysis of macroeconomic and financial variables as the dynamics of these variables are subject to periodic and systemic fluctuations over time. Pastpipatkul et al (2020) also affirmed that Markov switching models help to account for dynamic change in economic data because the economic factors exhibit varying levels of dependencies under different market conditions.…”

Section: Literature Reviewmentioning

confidence: 99%

Regime-Switching Determinants of Mutual Fund Performance in South Africa

2021

View full text Add to dashboard Cite

This study assesses the effect of fund-level and systemic factors on the performance of mutual funds in the context of changing market conditions. A Markov regime-switching model is used to analyze the performance of 33 South African equity mutual funds from 2006 to 2019. From the results, fund flow and fund size exert more predictive influences on performance in the bearish state of the market than in the bullish state. Fund age, fund risk, and market risk were found to be the most significant factors driving the performance of active portfolios under time-varying conditions of the market. These variables exert more influence on fund performance under bearish conditions than under bullish conditions, emphasizing the flight-to-liquidity assets phenomenon and risk-aversion behavior of fund contributors during unstable conditions of the market. Consequently, fund managers need to maintain adequate asset bases while implementing policies that minimize dispersions in fund returns to engender persistence in performance. This study provides novel perspectives on how the determinants of fund performance change with market conditions as portrayed by the adaptive market hypothesis (AMH).

show abstract

A Markov-Switching Model of Inflation in Bolivia

Cited by 11 publications

References 41 publications

Predicting Inflation—A Holistic Approach

Predicting Inflation—A Holistic Approach

Financial stability and monetary policy of the Central Bank of West African Countries: a Markov-Switching model

Regime-Switching Determinants of Mutual Fund Performance in South Africa

Contact Info

Product

Resources

About