According to a recent survey conducted in Vietnam, as of January 2023, over ** percent of respondents reported that inflation had a negative impact on them to some degree. In contrast, around **** percent of respondents said inflation did not have a negative effect on them.

This data-set cited sources that helped assess the interrelationship between savings, spending, and inflation expectations among undergraduate students. It was directed towards discovering the difficulties students may face with their finances because of inflation. A web-based survey was administered to 315 undergraduate students in Nigeria. Data obtained was analyzed using descriptive statistics such as percentage and frequency. The results revealed inflation expectations had a significant negative impact on the spending habits of students. The results further revealed that individual savings attitudes were reduced with an increase in inflation, but overall savings did not.

Under "Worldwide Inflation Based Database'' there are 4 sheets. Among them, the two are of data-sheets and the rest of the two are chart-typed sheets. However, between the two of the datasheets, one’s name is "Worldwide Inflation Rate in 2022”. Noted that this datasheet's table name is " Worldwide Inflation Rate in 2022''. Moreover, under this data table, there are three fields (“Country"; " Inflation rate-year over year"; "Date"), three columns, and, 185 rows. Also, each row contains 3 cells, and so, 185 rows contain 555 cells. And also, each column contains 185 cells, so, 3 columns contain 555 cells. In addition to, focusing on the two fields' ("Country", "Inflation rate-year over year") data of the datasheet.

"Inflation Rate of Countries" named "Line" type-based chart has been made. On this chart, “Country” field values are on the horizontal axis. Whereas, “Inflation rate-year over year” field values are on the vertical axis. However, the chart shows that Zimbabwe’s highest raking inflation, and its rate is 269%, and also, its time-scale continuity is up to on 22 October,2022. On the other hand, the negative scale of the inflation rate is in South Sudan which rate is -2.50, also, its time-scale is up to on 22 August,2022.

Basically, the chart has been made following “Data Shorting Descending Process’’, and, operating focused on the field (“Inflation rate-year over year’’) ‘s data.

And, another data sheet’s table name is “COUNTRY WISE INFLATION RTAE-2’’. This table contains two fields( “Country’’; “Inflation rate-year over year’’; ), 2 columns, 185 rows. Also, each row contain two cells, and so, 185 rows contain 370 cells. Whereas, each column contains 185 cells, and so, 2 columns contain 370 cells. However, on the basis of this datasheet, “Ascending typed Shorting Process” has been operated after the accomplishment of “Filtering” process. On the basis of it, “Inflation rate- year over year’’ named “line-type” chart has been created. On this chart, “Country” named field values are on horizontal axis, whereas, “Inflation rate-year over year “ named field values are on the vertical axis.

Be that as it may, the chart shows that South Sudan’s inflation rate is on the lower negative scale. In the opposite side, Lebanon’s inflation rate is at the highest level after Zimbabwe.

Cross-country regressions explaining output growth often obtain a negative effect from inflation. However, that result is not robust, due to the selection of countries in sample, temporal aggregation, and omission of consequential variables in levels. This paper demonstrates some implications of these mis-specifications, both analytically and empirically. In particular, for most G-7 countries, annual time series of inflation and the log-level of output are cointegrated, thus rejecting the existence of a long-run relation between output growth and inflation. Typically, output and inflation are positively related in these cointegrating relationships: a price markup model helps to interpret this surprising feature.

In a January 2025 survey on domestic travel in the United Kingdom, 23 percent of respondents planned to book cheaper accommodation services in the next six months due to the cost of living crisis. Looking for more free activities and spending less on eating out were other popular strategies planned by domestic travelers to save money.

Abstract The purpose of this study was to empirically verify the existence or not of a distortion in the comparability of information when inflationary effects are omitted from financial statements. Although inflation has been under control in Brazil since the Plano Real, with indices well below those recorded in the 1980s and 1990s, discussing the need for accounting recognition of the effects of inflation remains an extremely relevant and pertinent issue in light of the proposal of accounting to produce faithful information that closely reflects the economic reality in which organizations operate. The results of the research show that financial accounting has been directly affected by the omission of inflationary effects in financial statements, drawing attention to the negative effects this has caused on the quality of the information produced. In order to operationalize the research, the Balance Sheet Monetary Correction (BSMC) was applied to the balance sheets of Brazilian companies from the siderurgical and metallurgical sector listed on the BM&FBOVESPA in the period from 1996 to 2016. Based on the variables net income, return on equity (ROE), and return on assets (ROA), and two conceptual axes of comparability (between entities and between periods), the statistical parameters were developed and the hypotheses were defined, which were tested using the Student t parametric test. This article shows the damage caused to the decision-making process of the external users for whom financial statements are intended when these are prepared neglecting the effects of inflation. This is verifiable through the analyses of the results obtained, including the observation of significant distortions between the means of the corrected indicators and the means of the historical indicators, such as in the case of net income in 2001, 2002, 2012, 2013, 2014, and 2016 (33.98%, 91.92%, -65.54%, -30.01%, -53.59%, and 26.30% variation, respectively), of ROE (-67.16%, -61.43%, -53.06%, -63.46%, -133.81%, and 65.00% variations in 2008, 2009, 2010, 2011, 2014, and 2015, respectively), and of ROA (-26,70%, -41.14%, -33,34%, -43,49%, 98,83%, and -413,68% in 2005, 2009, 2010, 2011, 2012, and 2014, respectively).

The Consumer Price Index in the United States increased 0.10 percent in May of 2025 over the previous month. This dataset provides - United States Inflation Rate MoM - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset illustrates the median household income in East Side, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for East Side decreased by $12,682 (24.48%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 7 years and declined for 6 years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for East Side median household income. You can refer the same here

This paper exploits the term structure of interest rates to develop testable economic restrictions on the joint process of long-term interest rates and inflation when the latter is subject to a targeting policy by the central bank. In an empirical application to the Canadian inflation target zone, results indicate that financial markets perceive the band to be of approximately the same width as announced but asymmetrically distributed around the official target. This finding suggests that, in practice, the monetary authority might attach different weights to positive and negative inflation deviations from the target.

This study examined the relationship between debt servicing and foreign exchange rate unification in Nigeria from 1995 to 2023, hypothesizing that a unified exchange rate policy would significantly impact the country's debt service-to-revenue ratio. Using annual time series data from sources such as the International Monetary Fund and World Development Indicators, the study employed an Autoregressive Distributed Lag (ARDL) model to analyze the relationship between the debt service-to-revenue ratio and factors including the official foreign exchange rate, GDP growth rate, inflation rate, and oil prices. The findings revealed several notable insights. Exchange rate unification was found to have a significant negative effect on the debt service-to-revenue ratio, suggesting that a unified exchange rate policy could help reduce Nigeria's debt service burden. Both current and lagged inflation rates showed a significant negative impact on the debt service-to-revenue ratio, indicating that higher inflation might be eroding the real value of debt or increasing nominal revenues faster than debt servicing costs. Lagged exchange rates were found to negatively affect the debt service-to-revenue ratio, implying that higher exchange rates in the previous period decrease the current ratio. Oil prices demonstrated mixed effects, with current prices positively impacting the debt service-to-revenue ratio while lagged prices had a negative effect. The study also revealed strong persistence in debt servicing behavior over time, as evidenced by the significant positive correlation between current and previous year's debt service ratios. These results offer significant implications for policymakers. The negative effect of exchange rate unification on the debt service-to-revenue ratio suggests that such a policy could improve efficiency in forex markets and reduce arbitrage opportunities, ultimately helping to reduce the debt service burden. The negative relationship between inflation and the debt service-to-revenue ratio indicates that higher inflation might be beneficial for debt servicing in the short term, though this should be interpreted cautiously given the potential negative consequences of high inflation. The mixed impact of oil prices reflects the complexity of Nigeria's oil-dependent economy, highlighting the need for economic diversification. The strong persistence in debt servicing commitments points to potential structural issues in debt management or lack of fiscal flexibility. Policymakers can use these findings to inform strategies for managing Nigeria's debt burden. The results suggest that pursuing exchange rate unification, carefully managing inflation, diversifying the economy to reduce oil dependence, and improving fiscal discipline could all contribute to better management of debt servicing costs. However, it's crucial to consider the lagged effects of economic variables on debt servicing when formulating long-term fiscal strategies.

Inflation Rate in Japan decreased to 3.50 percent in May from 3.60 percent in April of 2025. This dataset provides the latest reported value for - Japan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The enduring discourse regarding the effectiveness of interest rate policy in mitigating inflation within developing economies is characterized by the interplay of structural and supply-side determinants. Moreover, extant academic literature fails to resolve the direction of causality between inflation and interest rates. Nevertheless, the prevalent adoption of interest rate-based monetary policies in numerous developing economies raises a fundamental inquiry: What motivates central banks in these nations to consistently espouse this strategy? To address this inquiry, our study leverages wavelet transformation to dissect interest rate and inflation data across a spectrum of frequency scales. This innovative methodology paves the way for a meticulous exploration of the intricate causal interplay between these pivotal macroeconomic variables for twenty-two developing economies using monthly data from 1992 to 2022. Traditional literature on causality tends to focus on short- and long-run timescales, yet our study posits that numerous uncharted time and frequency scales exist between these extremes. These intermediate scales may wield substantial influence over the causal relationship and its direction. Our research thus extends the boundaries of existing causality literature and presents fresh insights into the complexities of monetary policy in developing economies. Traditional wisdom suggests that central banks should raise interest rates to combat inflation. However, our study uncovers a contrasting reality in developing economies. It demonstrates a positive causal link between the policy rate and inflation, where an increase in the central bank’s interest rates leads to an upsurge in price levels. Paradoxically, in response to escalating prices, the central bank continues to heighten the policy rate, thereby perpetuating this cyclical pattern. Given this observed positive causal relationship in developing economies, central banks must explore structural and supply-side factors to break this cycle and regain control over inflation.

Using annual time series data for Ghana, the current study investigates the effect of inflation on manufacturing sector productivity for the period 1968-2013. The empirical verification is done by using the Johansen test (JT), the Vector Error Correction Model (VECM), and the Ordinary Least Squares (OLS) regression test. The results indicate significant stable long run relationship between inflation and manufacturing sector productivity. However, there is insignificant short run link between inflation and manufacturing sector productivity in the VECM. The results of the OLS test indicate negative significant link between inflation and manufacturing sector productivity. The findings suggest that inflation has led to a decrease in manufacturing sector productivity. Policy makers should manage inflation very well in order to improve manufacturing sector productivity. Future study should examine the current topic accounting for causality and structural breaks issues since the present study did not consider these issues.

Inflation Rate in Germany decreased to 2 percent in June from 2.10 percent in May of 2025. This dataset provides the latest reported value for - Germany Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

About this dataset

Context

The dataset illustrates the median household income in East Side, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2021, the median household income for East Side increased by $23,882 (48%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 7 years and declined for 4 years.

https://i.neilsberg.com/ch/east-side-pa-median-household-income-trend.jpeg" alt="East Side, PA median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2021
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for East Side median household income. You can refer the same here

Results of post estimation diagnostic and stability tests.

Inflation Rate in Russia decreased to 9.40 percent in June from 9.90 percent in May of 2025. This dataset provides - Russia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset illustrates the median household income in East Side township, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for East Side township increased by $19,360 (37.58%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 8 years and declined for 5 years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for East Side township median household income. You can refer the same here

Inflation Rate in India decreased to 2.82 percent in May from 3.16 percent in April of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in Iran increased to 38.90 percent in April from 37.10 percent in March of 2025. This dataset provides the latest reported value for - Iran Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.