Conducting Causal Analysis by Means of Approximating Probabilistic Truths

The current paper develops a probabilistic theory of causation using measure-theoretical concepts and suggests practical routines for conducting causal inference. The theory is applicable to both linear and high-dimensional nonlinear models. An example is provided using random forest regressions and daily data on yield spreads. The application tests how uncertainty in short- and long-term inflation expectations interacts with spreads in the daily Bitcoin price. The results are contrasted with those obtained by standard linear Granger causality tests. It is shown that the suggested measure-theoretic approaches do not only lead to better predictive models, but also to more plausible parsimonious descriptions of possible causal flows. The paper concludes that researchers interested in causal analysis should be more aspirational in terms of developing predictive capabilities, even if the interest is in inference and not in prediction per se. The theory developed in the paper provides practitioners guidance for developing causal models using new machine learning methods that have, so far, remained relatively underutilized in this context.

Forecasting and Technical Comparison of Inflation in Turkey With Box-Jenkins (ARIMA) Models and the Artificial Neural Network

Inflation refers to an ongoing and overall comprehensive increase in the overall level of goods and services price in the economy. Today, inflation, which is attempted to be kept under control by central banks or, in the same way, whose price stability is attempted, consists of continuous price changes that occur in all the goods and services used by the consumers. Undoubtedly, in terms of economy, in addition to the realized inflation, inflation expectations are also gaining importance. This situation requires forecasting the future rates of inflation. Therefore, reliable forecasting of the future rates of inflation in a country will determine the policies to be applied by the decision-makers in the economy. The aim of this study is to predict inflation in the next period based on the consumer price index (CPI) data with two alternative techniques and to examine the predictive performance of these two techniques comparatively. Thus, the first of the two main objectives of the study are to forecast the future rates of inflation with two alternative techniques, while the second is to compare the two techniques with respect to statistical and econometric criteria and determine which technique performs better in comparison. In this context, the 9-month inflation in April-December 2019 was forecast by Box-Jenkins (ARIMA) models and Artificial Neural Networks (ANN), using the CPI data which consist of 207 data from January 2002 to March 2019 and the predictive performance of both techniques was examined comparatively. It was observed that the results obtained from both techniques were close to each other.

Central Bank Credibility During COVID-19: Evidence from Japan

Japanese realized and expected inflation has been below the Bank of Japan’s two percent target for many years. We use the exogenous COVID-19 pandemic shock to examine the efficacy of monetary and fiscal policy responses for elevating inflation expectations from an arbitrage-free term structure model of nominal and real yields. We find that monetary and fiscal policy announcements during this period failed to lift inflation expectations, which instead declined notably and are projected to only slowly revert back to levels far below the announced target. Hence, our results illustrate the challenges faced in raising well-anchored low inflation expectations.

A revival of money velocity would pressure the US Fed

Significance The debate about how transitory this inflation is will persist. One way to consider the phenomenon is to examine the velocity of money -- the ratio of nominal GDP to monetary aggregate M1 or M2 -- which measures how many times money is changing hands, reflecting the willingness of consumers and businesses to engage in economic transactions. Money velocity remains modest but, if it rises, inflation pressures will also rise. Impacts The extent to which pandemic-related behavioural changes persist will shape the longer-term economic outlook and change many sectors. The Fed's communication policy will be key to calming markets; research shows that it has successfully anchored inflation expectations. Two years after COVID-19 was first known to be circulating, its spread remains the largest influence on the economic outlook.

Inflation expectations matter more than unemployment

Significance The surge in inflation this year owes more to supply bottlenecks caused by the release of pent-up demand than to falling unemployment. In the decade before the pandemic, US unemployment more than halved and euro-area unemployment nearly halved, but inflation remained below target in both economic areas. Impacts Central banks face the dilemma of raising rates too early for growth and too late for inflation, and may struggle to dampen expectations. The threat of a possible revival of the pandemic will help temporarily to cool inflation expectations that have surged in 2021. The trade-off between unemployment and inflation that has been missing for many years may emerge again once the pandemic is finally over.

The dynamics of survey-based household inflation expectations in India

PurposeThe authors analyze households' inflation expectations data for India, collected quarterly by the RBI for more than a decade. The contribution of this paper lies in two folds. First, this study examines the relationship between relatively recent inflation expectations survey of households (IESH) and the actual inflation for India. Secondly, the authors employ a structural VAR with the time period 2006 Q2 to 2020 Q2 on inflation expectation survey data of India. A short-term non-recursive restriction is imposed in the model in order to capture the simultaneous co-dependence causal effect of inflation expectation and realized inflation.Design/methodology/approachThis paper studies the dynamic behavior of inflation expectations survey data in two folds. First, the authors analyze the time series property of the survey data. The authors begin with testing the stationarity property of the series, followed by the casual relationship between the expected and actual inflation. The authors further examine the short-run and long-run behavior of the IESH with actual inflation. Employing autoregressive distributed lag and Johansen co-integration, the authors tested if a long-run relationship exists between the variables. In the second approach, the authors investigate the determinants of inflation expectations by employing a non-recursive SVAR model.FindingsThe preliminary explanatory test reveals that inflation expectation is a policy variable and should be used in monetary policy as an instrument variable. The model identifies the price puzzle for India. The authors find that the response of inflation to a monetary policy shock is neutral. The results also indicate that the expectations of the general public are self-fulfilling.Originality/valueIESH has only commenced from September 2005, hence is relatively new as compared to other survey in developed countries. Being a new data set so far, the authors could not locate any study devoted in analyzing the behavior of the data with other macroeconomic variables.

Eight New Challenges Faced by Global Economy

Due to COVID-19, the world has experienced the most severe economic recession since the Second World War. Some "unconventional" monetary policies have been enforced in order to stimulate the economy, and their effectiveness is positively regarded by the IMF. However, this paper identifies two negative effects of these measures. Firstly, they exacerbate policy instability; secondly, they will be detrimental to the fundamentals of monetary policies in the long term. In addition, the world economy is also confronted with many challenges, including global inflation expectations, the trends of dollar as a currency, restructuring of global supply chain, volatility of asset prices and commodity prices, and global and regional governance.