Personal Consumption Expenditures Research Articles

The long and variable lags of monetary policy: Evidence from disaggregated price indices

We study how monetary policy affects subcomponents of the Personal Consumption Expenditures Price Index (PCEPI) using local projections. Following a monetary policy contraction, the response of aggregate PCEPI turns significantly negative after over three years. There are stark differences in the timing and magnitude of the responses across price categories, including some prices that show an initially positive response. We discuss theoretical interpretations of our findings and point to useful directions for future theoretical research. We also show how to re-aggregate our cross-sectional estimates and their standard errors, taking into account dependence between different prices using a Seemingly Unrelated Regression approach. Re-aggregation exercises show that changes in expenditure behavior have not accelerated the long-lagged response of inflation to monetary policy.

Research on the relationship between global oil prices and economic indicators based on linear regression and ARIMAX models

This report aims to analyze the relationship between global oil prices and various economic indexes by using linear regression and ARIMAX models. This study will predict global oil prices accurately and establish a reasonable system for regulating oil prices. The research uses the statistical approach to predict oil prices based on historical data (including independent variables and dependent variable). The study uses monthly average data of WTI crude oil prices from January 2000 to March 2023 and contains the analysis of various economic indicators such as Consumer Price Index (CPI), Personal Consumption Expenditures (PCE), Employment, Population, and Oil Price. The findings indicate that the linear regression model can explain about 40.89% of the variation in log oil price, with significant negative effects of log_PCE, log_EMPLOYMENT, and log_POPULATION, and a significant positive effect of CPI on log_price. However, there exists the probability that some other factors have impact on oil prices. In this study, the author employ the ARIMAX model with ARIMA(4,1,1) errors, which can describe a relatively good fit and small errors in training set measures. Overall, while the linear regression model partially explains the variability in global oil prices, further analysis on residuals is necessary. The study concludes that the ARIMAX model provides a better approach to capture the time-series nature of the data.

A distributional approach to U.S. personal consumption expenditures: an overview

A distributional approach to U.S. personal consumption expenditures: an overview

Post‐COVID inflation dynamics: Higher for longer

AbstractWe implement a novel nonlinear structural model featuring an empirically successful frequency‐dependent and asymmetric Phillips curve; unemployment frequency components interact with three components of core personal consumption expenditures (PCE)—core goods, housing, and core services ex‐housing—and a variable capturing supply shocks. Forecast tests verify accuracy in its unemployment–inflation trade‐offs, crucial for monetary policy. Using this model, we assess the plausibility of the December 2022 Summary of Economic Projections (SEP). By 2025Q4, the SEP projects 2.1% inflation; however, conditional on the SEP unemployment path, we project 2.9%. A fairly deep recession delivers the SEP inflation path, but a simple welfare analysis rejects this outcome.

Using deep (machine) learning to forecast US inflation in the COVID‐19 era

AbstractThe 2021–2022 surge in US inflation was unanticipated by the Survey of Professional Forecasters (SPF) and other macroeconomists and institutions. This study assesses whether nascent deep learning frameworks and methods more accurately project recent core personal consumption expenditures inflation. We create a recurrent neural network (RNN) to forecast long‐term inflation, and after training on 60 years of quarterly data, the model outperforms the SPF and projects a spike in inflation similar to that of recent years. We compare the model's performance with and without COVID‐19–specific data and discuss some implications of our findings for economic forecasting in global crises.

Research on the Impact of American Consumer Behavior after COVID-19

The spread of COVID-19 has significantly influenced people’s lives and brought worldwide recession. In order to society to recover faster from the epidemic, the first step is to understand the impact of the epidemic on people and changes in people's consumption habits. This paper uses the Real Personal Consumption Expenditure provided by Fred to categorize consumption into service, durable goods, and non-durable goods and to analyze the change of consumption focus of citizens. After the epidemic, overall consumption dropped, and it took almost a year to recover to the previous stage. After COVID-19, consumers are less willing to spend on service and this is the part that the government needs to put most effort on. After analyzing consumers’ consumption behavior, the government can make suitable policies to encourage consumption activities.

A study of macroeconomic variables that effected employment in the United States from 1948 to 2021

The paper provides an analysis of important U.S. macroeconomic variables that effect aggregate employment. The paper seeks to answer the question “What are the deter¬minants of changes in aggregate employment in the United States of America (U.S.)?” This is an important research topic because significant increases in unemployment can have a profound effect on an entire society, not just on its unemployed workers. When employment declines, public health declines, crime increases, suicides increase, and public revenues decrease. This paper uses quarterly data from 1948-2021 to estimate the effect of important macroeconomic variables on aggregate employment. The macroeconomic variables include personal consumption expenditures, U.S. federal government expenditures, nominal GNP, international trade (imports plus exports), M3 money stock, the mini-mum wage level, non-residential fixed investment, non-manufacturing employment, and U.S. federal tax receipts.

Прогноз мировых цен нефти на основе монетарной политики Соединённых Штатов Америки

This study explores the critical realm of forecasting oil prices within the global energy resources market. The research is particularly timely as it provides new insights into the future growth prospects of Brent crude oil prices, which are increasingly influenced by the indicators of the monetary policy set forth by the USA Federal Reserve. The primary objective of this scientific endeavor is to predict Brent crude oil prices in response to shifts in the indicators of the US Federal Reserve's monetary policy. To fulfill this objective, the study systematically tackled several key tasks. These tasks encompassed a thorough examination of the theoretical foundations underpinning oil price forecasting, the meticulous compilation of statistical data related to the target indicators, and the application of specialized economic methodologies. Mul[1]tiple linear regression equations were formulated to establish the relationship be[1]tween Brent crude oil prices and the indicators of the US Federal Reserve's monetary policy. Furthermore, the study ventured into the prediction of these Federal Reserve indicators and arrived at substantive conclusions. The research methodology employed a range of general and specialized scientific techniques, encompassing analysis, synthesis, and statistical analysis. Notably, the scientific innovation of this study lies in the construction of multiple linear regres[1]sion equations to forecast Brent crude oil prices, hinging on key indicators of the USA Federal Reserve's monetary policy, including the effective federal funds rate, the M2 monetary aggregate, the US dollar index, the core personal consumption expenditure price index, and the US unemployment rate. Additionally, this study cal[1]culated an increasing trend equation for the M2 monetary aggregate in the United States. The practical implications of this research are profound, offering valuable insights for investors looking to craft effective trading strategies within the global energy resources market.

Excess Savings and Consumer Behavior: Excess Compared to What?

How much accumulated savings do households hold, and what do these savings imply about future consumption? Economists typically consider excess savings when gauging the level of savings that households may use to maintain real consumption as costs rise. Economists have estimated strikingly different levels of currently held excess savings. We highlight the differences between measures of counterfactual savings—that is, the amount of savings households would be expected to hold barring unusual events—and their relevance in computing post pandemic excess savings. Furthermore, we show that, using counterfactual savings that rely on the idea of consumption smoothing, excess savings are currently positive in the case that households assume that recent income losses are transitory. These findings carry additional implications for expected personal consumption expenditure patterns.

Thực trạng thu chi tài chính tại Trung tâm Y tế huyện Đăk Glong tỉnh Đăk Nông, giai đoạn 2018 – 2021

Objectives: The study was conducted to describe the status of financial revenue and expenditure at the Dak Glong District Health Center, Dak Nong Province from 2018 to 2021. Method: A cross-sectional study used retrospective secondary data from this health center's financial reports. Results: Research results showed that the total revenue of the center increased in the period 2018-2021, with non-business revenue accounted for from 42 to 65,9% of the total revenue each year. Revenue from hospital fees and health insurance accounted for a high proportion of 97%-99% of the total non-business revenue. The total expenditure of the center increased in the period 2018-2021. Frequent expenditure contributes the highest proportion of all, making up for more than 90%, while expenditure on major repairs and procurement of fixed assets accounts for a relatively low proportion, ranging from 4 to 4. 7% of total spending per year. Personal consumption expenditure accounts for more than 50% of the total recurrent expenditure at the center and witnesses the upward trend each year. Conclusions: In the period of 2018-2021, the differences between revenue and expenditure of the center increased but was not stable. The center has made appropriations for funds, the total amount of funds has tended to increase but is not stable, due to autonomously finance management, especially after the merger, with a variety of mechanisms and policies, along with the situation of the COVID-19 epidemic in 2020-2021. These altogether causes certain challenges for the center in balancing the revenue and expenditure. Key words: Financial revenue and expenditure, The Medical Center of Dak Glong District.

The impact of the monetary policy of the Federal Reserve System of the United States on world oil prices

The relevance of the presented scientific research lies in the search for new data on foreign economic factors that can change world oil prices. The purpose of the study is to predict the prices of Brent crude oil based on the impact of new external economic factors, because the influence of supply and demand in the energy market has significantly weakened. To achieve the purpose of the study, the following tasks were solved: the theoretical foundations of the oil market were considered; a methodological approach to forecasting world oil prices was selected; as a result, an equation of multiple linear regression with independent variables in the form of indicators of the monetary policy of the United States is constructed, which makes it possible to make a forecast of world oil prices. The research involves general and special scientific methods: analysis, synthesis, monographic, statistical (graphical, tabular, centered moving average method, correlation and regression analysis). The scientific novelty of the study is as follows: based on statistical data on Brent crude oil prices, the effective federal funds rate of the US Federal Reserve, the M2 monetary aggregate in the US, the US dollar index, the US core personal consumption expenditure price index, the unemployment rate in the US for the period January 2014 January 2023, the equation is constructed multiple linear regression with the function of forecasting Brent crude oil prices. The above equation of multiple linear regression reflects the noticeable influence of the monetary policy of the US Federal Reserve System on world oil prices.

The Keynesian Stimulus Model: Stimulating Economic Activities with Direct Transfers

Governments use direct transfers as a fiscal measure to stimulate economic activities during shocks. As COVID-19 continues to ravage economies globally, governments worldwide have responded with fiscal and monetary policies to manage the pandemic’s economic impact. In addition, the U.S. government has intervened with direct transfers to provide liquidity to prevent a prolonged shock. However, opinions are divided on the efficacy of the Keynesian stimulus policy. This study used a mixed-method research design to analyze the classical Keynesian model and compares it with the monetarist model to provide insight into the stimulus policy outcomes of the Coronavirus Aid Relief and Economic Security (CARES) Act of 2020 and subsequent policies used to manage the COVID-19 shock. Time-series data from the Bureau of Economic Analysis (BEA), Bureau of Labor Statistics (BLS), and the Federal Reserve Bank (the Fed) of the percentage changes in GDP, disposable personal income (DPI), and personal consumption expenditure (PCE), as well as unemployment rates (UR), interest rates (INT), and inflation rates (IFL), were collected and analyzed. The study used multiple regression (MR) to empirically examine the variables' relationships to ascertain both models’ short-term efficacy. The results suggest that DPI, PCE, and UR significantly predicted the percentage change in GDP in the Keynesian model, whereas, UR, INT, and IFL did not substantially predict the change in GDP in the monetarist model.

Consumption and tax gains attributable to Covid-19 vaccinations in 12 EU countries with low vaccination rates.

The Covid-19 pandemic is an economic and a health crisis. Households reduced consumption expenditures as large-scale physical distancing measures, lower disposable incomes and fear of infection when engaging in many types of economic activity took hold. This, in turn, reduced domestic tax revenues at a time when governments were facing increased financial pressures to strengthen and sustain welfare states. We developed a simulation model, the Covid-19 Taxination Simulator, to estimate potential economic gains and tax revenues attributable to vaccine rollouts. We apply the model to 12 European Union countries which had low vaccination rates at the beginning of 2022. The highest growth in aggregate personal consumption expenditure attributable to Covid-19 vaccines administered as of January 2022 is in Greece (10.8%), Slovenia (8.6%) and Czechia (8.6%), while the lowest is in Bulgaria (2.2%) and Slovakia (2.1%). If countries had vaccinated 85% of their adult population, the largest gains in consumption tax revenues would be expected in Romania (830 million Euros) and Poland (738 million Euros). Consumption tax revenues generated by meeting the 85% of the adult population target would, on their own, be large enough to fully cover the costs of expanding the vaccine rollout itself in Estonia, Latvia, Slovenia, Croatia, Czechia, Hungary and Greece. Covid-19 vaccination rollouts not only save lives and relieve pressures on health systems, they also support economic growth and generate additional tax revenues. These revenues can partially offset the costs of vaccines programmes themselves.

National expenditures on local amenities

We develop a framework for estimating Americans' implicit expenditures on spatially varying nonmarket amenities. We focus on location-specific factors that affect the quality of life but are not formally traded. Examples include climate, geography, pollution, local public goods, and transportation infrastructure. Households pay for residential access to these amenities indirectly, through housing prices, wages and property taxes. We construct a database of 75 amenities, match it to 5 million households' location choices, and use hedonic methods to estimate their total amenity expenditures. Our benchmark estimate for the year 2000 is $562 billion--equivalent to 8% of Americans’ personal consumption expenditures.

Cost-Effectiveness of Azacitidine and Ivosidenib in Newly Diagnosed Older, Intensive Chemotherapy-Ineligible Patients with IDH1-Mutant Acute Myeloid Leukemia

Introduction Ivosidenib (IVO) is an oral inhibitor of mIDH1 that is approved in the USA as monotherapy for pts with mIDH1AML, either relapsed/refractory or newly diagnosed, but older/unfit for intensive therapy. The recent AGILE trial (Montesinos et al. NEJM 2022) randomized newly diagnosed, older/intensive chemotherapy-ineligible mIDH1 AML pts to IVO + AZA vs placebo + AZA and showed improved event-free survival (EFS) and overall survival (OS) in the intervention arm. We sought to understand the health economic implications by conducting a cost-effectiveness analysis. Methods Pts with newly diagnosed mIDH1 AML entered our partitioned survival model at age 75 years and received either IVO/AZA or AZA monotherapy. We used recreated pt-level data derived from the Kaplan-Meier curves and at-risk tables for EFS and OS from the AGILE trial for the IVO/AZA arm to fit loglogistic parametric survival distributions. Hazard ratios (HRs) for EFS and OS were used to derive the EFS and OS curves for the AZA arm, respectively. Medication costs were derived from the average sales price (ASP) for AZA and cytarabine listed by the Centers for Medicare and Medicaid Services or the average wholesale price (AWP) for IVO and venetoclax (Ven), respectively. As ASP ranges between 26-30% below the AWP, we used a 28% discount off the AWP for the base-case scenario and varied this discount during sensitivity analyses between 18% and 38%. Costs and practice patterns of treatment discontinuation or treatment interruption due to adverse events, subsequent treatments, supportive and terminal care, and incidence of complications were derived from the original trial or published literature (Table 1). Costs were adjusted for inflation to 2021 US dollars using the personal consumption expenditure health index. Utilities were derived from the literature and were assumed to be equal between treatment arms for the base case scenario as the quality-of-life assessment were not statistically significantly different for IVO/AZA vs AZA in the AGILE trial at most timepoints. Costs and utilities were modeled over a 30-year time horizon and discounted by 3% annually. Model outputs were used to calculate the incremental cost-effectiveness ratio (ICER) for IVO/AZA, which represents the cost in 2021 US dollars (USD) of each additional quality adjusted life-year (QALY) gained compared to AZA. One-way sensitivity analyses were performed to evaluate the impact of individual parameters on the overall model. Utility values were varied with a 10% range and all other variables were varied across a 50% range. We also performed probabilistic sensitivity analyses, in which we described each parameter using a distribution and performed 10,000 Monte Carlo simulations, each time randomly sampling from the distributions of model inputs. Results In the base case scenario, IVO/AZA and AZA resulted in life-time costs of $652,088 and $242,828, respectively, for an incremental cost of $409,260 with IVO/AZA. With an incremental gain of 2.21 QALYs with IVO/AZA (IVO/AZA: 3.10 QALYs; AZA: 0.89 QALYs), the ICER of IVO/AZA compared to AZA was $185,024/QALY. In one-way sensitivity analyses, only a reduction in the AWP of IVO by 32.4% (from $33,693 to $22,788 per 28-day cycle) would yield a reduction in the ICER to below the conventional willingness-to-pay (WTP) threshold of $150,000/QALY. Figure 1 shows the ten variables with the greatest influence on the ICER demonstrating that variations in any of the variables would not achieve an ICER of less than $150,000/QALY. Probabilistic sensitivity analysis yielded a median ICER of $205,124/QALY (95% CI: $129,344 - $346,479) with AZA favored in 91.2% of 10,000 iterations at a WTP threshold of $150,000/QALY. Conclusion Even in the best-case scenario in favor of the IVO arm following AGILE trial assumptions, we calculated an ICER of $185,024/QALY, which makes IVO/AZA unlikely to be cost-effective compared to AZA alone when applying the traditional WTP threshold of $150,000/QALY in patients with newly diagnosed mIDH1 AML. Only a reduction in the price of IVO by 32.4% lowered the ICER to below $150,000/QALY. The influence of more frequent use of 2nd line IVO in the control arm, comparison against an AZA-Ven control arm, differences in utilities, and extended duration of follow up in the prematurely terminated trial on the ICER warrant additional analyses but are likely to further worsen the cost effectiveness of IVO. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Analysis of Educational Migration Decision in Indonesia

Generally, migration is the movement of a person from one to another region. Besides that, several factors may cause migration such as uneven economic and educational development. This study aims to discover the factors of educational migration, particularly in Indonesia. This study carried out Indonesian Family Life Surveys (IFLS) microdata; however, the IFLS divides into IFLS wave 3 (2000), IFLS wave 4 (2007), and IFLS wave 5 (2014). Hence, the total sample of the study is 1.878 people. In addition, The Logistics Regression Model or Logit Model analysis technique is used in this study. This study found that educational migration factors are influenced by personal consumption expenditure (PCE), geographical conditions, gender, high school education, university education, age, religion, cognitive ability, father's educational background (High School and university), mother's educational background (High School and university), and the province of origin. To sum up, the future welfare of a person is influenced by educational migration.
 
 
 Received: 8 August 2022 / Accepted: 10 October 2022 / Published: 5 November 2022

Raiders of the lost high‐frequency forecasts: New data and evidence on the efficiency of the Fed's forecasting

SummaryWe introduce a new dataset of real gross domestic product (GDP) growth and core personal consumption expenditures (PCE) inflation forecasts produced by the staff of the Board of Governors of the Federal Reserve System. In contrast to the eight Greenbook forecasts a year the staff produce for Federal Open Market Committee (FOMC) meetings, our dataset has roughly weekly forecasts. We use these data to study whether the staff forecasts efficiently. Prespecified regressions of forecast errors on forecast revisions show the staff's GDP forecasts exhibit time‐varying inefficiency between FOMC meetings, and also show some evidence for inefficient inflation forecasts.

Accelerating the Improvement of Human Well-Being in China through Economic Growth and Policy Adjustment.

Human well-being in many countries lags behind the gross domestic product (GDP) due to the rapid changes in the socio-economic environment that have occurred for decades. However, the mechanisms behind this complex phenomenon are still unclear. This study revealed the changes in human well-being in China from 1995 to 2017 by revising the genuine progress indicator (GPI) at the national level and further quantified the contribution of interfering factors that have driven the increase in the GPI. The results indicated that: (1) The per capita GPI of China showed an increasing trend with an annual growth rate of 12.43%. The changes in the GPI followed the same pattern as economic development, rather than presenting the phenomenon of economic growth combined with a decline in welfare that has been recorded in some countries and regions. (2) The increase in human well-being was mainly driven by economic growth, but it was most sensitive to social factors. (3) Increasing income inequality and the cost of lost leisure time contributed obvious negative impacts (24.69% and 23.35%, respectively) to the per capita GPI. However, the increase in personal consumption expenditures, the value of domestic labor, ecosystem service value, and net capital growth accelerated the rise in the GPI, with positive contribution rates of 30.69%, 23%, 20.54%, and 20.02%, respectively. (4) The continuous increase in economic investment and the strengthening of social management due to policy adjustments completely counteracted the negative impacts on human well-being, thus leading to a great increase in the per capita GPI. Such insights could provide theoretical support for decision making and policy implementation to improve global human well-being.

Decomposing Supply and Demand Driven Inflation

The extent to which either supply or demand factors drive inflation has important implications for economic policy. I propose a framework to decompose inflation into supply- and demand-driven components. I generate two new data series, the supply and demand-driven contributions to personal consumption expenditures (PCE) inflation, which quantify the degree to which either demand or supply is driving inflation in a current month. The series show expected time-series patterns. The demand-driven contribution tends to decline during recessions, while the supply-driven contribution tends to follow food and energy prices. Monetary policy tightening acts to reduce the demand-driven contribution of inflation. Oil-supply shocks act to increase the supply driven contribution, but decrease the demand-driven contribution of inflation. The decompositions can be used to test theory or by policymakers and practitioners to track inflation drivers in real time.

Influence of Government Expenditure on Economic Growth: An Empirical Retrospection Based on ARDL Approach

The study investigates the influence of government expenditure (GE) on Oman’s economic growth by examining different government-spending dimensions as predictors of economic progression based on collected time-series data of Oman for 30 years. The study uses ‘Auto-Regressive Distributed Lag’ (ARDL) to assess the short-range and long-term effects of the dimensions on economic growth. GE, personal consumption expenditure and public debt are significant negative predictors of Oman’s economic progress in the long run. However, government and private consumption expenditures (PCEs) are significantly negative in the short run. Gross domestic investment is not a significant predictor in the long run, whereas public debt is a substantial positive predictor of Oman’s economic growth in the short run. The study will help policymakers recognize GE in Oman’s economic progression and development.