This data package includes the underlying data to replicate the charts and calculations presented in US Monetary Policy and the Recent Surge in Inflation, PIIE Working Paper 24-13.

If you use the data, please cite as:

Reifschneider, David. 2024. US Monetary Policy and the Recent Surge in Inflation. PIIE Working Paper 24-13. Washington: Peterson Institute for International Economics.

The Federal Reserve's balance sheet has undergone significant changes since 2007, reflecting its response to major economic crises. From a modest 0.9 trillion U.S. dollars at the end of 2007, it ballooned to approximately 6.76 trillion U.S. dollars by March 2025. This dramatic expansion, particularly during the 2008 financial crisis and the COVID-19 pandemic - both of which resulted in negative annual GDP growth in the U.S. - showcases the Fed's crucial role in stabilizing the economy through expansionary monetary policies. Impact on inflation and interest rates The Fed's expansionary measures, while aimed at stimulating economic growth, have had notable effects on inflation and interest rates. Following the quantitative easing in 2020, inflation in the United States reached eight percent in 2022, the highest since 1991. However, by November 2024, inflation had declined to 2.7 percent. Concurrently, the Federal Reserve implemented a series of interest rate hikes, with the rate peaking at 5.33 percent in August 2023, before the first rate cut since September 2021 occurred in September 2024. Financial implications for the Federal Reserve The expansion of the Fed's balance sheet and subsequent interest rate hikes have had significant financial implications. In 2023, the Fed reported a negative net income of 114.3 billion U.S. dollars, a stark contrast to the 58.84 billion U.S. dollars profit in 2022. This unprecedented shift was primarily due to rapidly rising interest rates, which caused the Fed's interest expenses to soar to over 281 billion U.S. dollars in 2023. Despite this, the Fed's net interest income on securities acquired through open market operations reached a record high of 174.53 billion U.S. dollars in the same year.

The U.S. federal funds effective rate underwent a dramatic reduction in early 2020 in response to the COVID-19 pandemic. The rate plummeted from 1.58 percent in February 2020 to 0.65 percent in March, and further decreased to 0.05 percent in April. This sharp reduction, accompanied by the Federal Reserve's quantitative easing program, was implemented to stabilize the economy during the global health crisis. After maintaining historically low rates for nearly two years, the Federal Reserve began a series of rate hikes in early 2022, with the rate moving from 0.33 percent in April 2022 to 5.33 percent in August 2023. The rate remained unchanged for over a year, before the Federal Reserve initiated its first rate cut in nearly three years in September 2024, bringing the rate to 5.13 percent. By December 2024, the rate was cut to 4.48 percent, signaling a shift in monetary policy in the second half of 2024. The first rate cut in 2025 then set the rate at 4.33 percent. What is the federal funds effective rate? The U.S. federal funds effective rate determines the interest rate paid by depository institutions, such as banks and credit unions, that lend reserve balances to other depository institutions overnight. Changing the effective rate in times of crisis is a common way to stimulate the economy, as it has a significant impact on the whole economy, such as economic growth, employment, and inflation. Central bank policy rates The adjustment of interest rates in response to the COVID-19 pandemic was a coordinated global effort. In early 2020, central banks worldwide implemented aggressive monetary easing policies to combat the economic crisis. The U.S. Federal Reserve's dramatic reduction of its federal funds rate - from 1.58 percent in February 2020 to 0.05 percent by April - mirrored similar actions taken by central banks globally. While these low rates remained in place throughout 2021, mounting inflationary pressures led to a synchronized tightening cycle beginning in 2022, with central banks pushing rates to multi-year highs. By mid-2024, as inflation moderated across major economies, central banks began implementing their first rate cuts in several years, with the U.S. Federal Reserve, Bank of England, and European Central Bank all easing monetary policy.

Key information about United States Policy Rate

• United States cash rate (Policy Rate: Month End: Effective Federal Funds Rate) was set at 4.33 % pa in Feb 2025, compared with 4.33 % pa in the previous Jan 2025.
• US Policy Rate averaged 4.33 % pa and is updated monthly, available from Jul 1954 to Feb 2025.
• The data reached an all-time high of 22.00 % pa in Dec 1980 and a record low of 0.04 % pa in Dec 2011.

• In the latest reports, US Short Term Interest Rate: Month End: Treasury Bills: 3 Months was reported at 4.20 % pa in Feb 2025.
• Its Long Term Interest Rate (Treasury Notes Yield: Constant Maturity: Nominal: 10 Years) was reported at 4.45 % pa in Feb 2025.
• Its Real Effective Exchange Rate was 122.45 in Jan 2025.

The U.S. federal funds rate peaked in 2023 at its highest level since the 2007-08 financial crisis, reaching 5.33 percent by December 2023. A significant shift in monetary policy occurred in the second half of 2024, with the Federal Reserve implementing regular rate cuts. By December 2024, the rate had declined to 4.48 percent. What is a central bank rate? The federal funds rate determines the cost of overnight borrowing between banks, allowing them to maintain necessary cash reserves and ensure financial system liquidity. When this rate rises, banks become more inclined to hold rather than lend money, reducing the money supply. While this decreased lending slows economic activity, it helps control inflation by limiting the circulation of money in the economy. Historic perspective The federal funds rate historically follows cyclical patterns, falling during recessions and gradually rising during economic recoveries. Some central banks, notably the European Central Bank, went beyond traditional monetary policy by implementing both aggressive asset purchases and negative interest rates.

This dataset is about book subjects and is filtered where the books is Uncertainty and monetary policy rules in the United States. It has 10 columns such as authors, average publication date, book publishers, book subject, and books. The data is ordered by earliest publication date (descending).

This data package includes the underlying data to replicate the charts, tables, and calculations presented in Fiscal policy and the pandemic-era surge in US inflation: Lessons for the future, PIIE Working Paper 24-22.

If you use the data, please cite as:

Dynan, Karen, and Douglas Elmendorf. 2024. Fiscal policy and the pandemic-era surge in US inflation: Lessons for the future. PIIE Working Paper 24-22. Washington: Peterson Institute for International Economics.

United States US: Discount Rate: End of Period data was reported at 1.500 % pa in 2017. This records an increase from the previous number of 1.250 % pa for 2016. United States US: Discount Rate: End of Period data is updated yearly, averaging 4.500 % pa from Dec 1950 (Median) to 2017, with 68 observations. The data reached an all-time high of 12.870 % pa in 1980 and a record low of 0.500 % pa in 2009. United States US: Discount Rate: End of Period data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s United States – Table US.IMF.IFS: Money Market and Policy Rates: Annual.

In this paper we model and explain US macroeconomic outcomes subject to the discipline that monetary policy is set optimally. Exploiting the restrictions that come from optimal policymaking, we estimate the parameters in the Federal Reserve's policy objective function together with the parameters in its optimization constraints. For the period following Volcker's appointment as chairman, we estimate the implicit inflation target to be around 1.4% and show that policymakers assigned a significant weight to interest rate smoothing. We show that the estimated optimal policy provides a good description of US data for the 1980s and 1990s.

The study deals with the first 25 years of German monetary policy from 1948 to 1973 in the so called “Bretton Woods Era”. There is a focus on the attitude of the banks of the German states and on the German Central Bank. This attitude is presented in two different ways: (1) descriptive presentation of intentions, measures and impact of the behavior of the central bank based on annual and monthly reports of this institution; (2) economic time series analysis especially “cointegration analysis” which helps to identify and quantify determinants and impacts of monetary policy. First, an overview over monetary policy and economic development between 1948 and 1973 is given connected with some conceptual annotations on monetary policy. Next a traditionally used investigation method of Germany economic history will be presented using a qualitative historical approach. The quantitative econometric approach illustrates a so far widely unattended aspect of German economic historiography. In the field of regression analysis of time series, econometric research produced new results. These methodological advances are applied in the regression analysis of this study. It will be shown that the formulation of a structural error correction model for the monetary area of the German Economy is able to confirm the theoretical statements on monetary policy in a small open economy with fixed exchange rates.

Lists of variables - Industry production - Real income - Population - Relative income level of the states compared to the USA - Real exports - Real investments - Gross domestic product-Inflator - Money supply - Real GDP - Price index of costs of living - Prices of consumer goods - Wholesale prices - Prices of export goods - DGP-deflator - Overnight rate - Monthly allowance rate - Ninety days´ loan rate
- US-American money market rate - US-American price index
- Nominal DM/Dollar-exchange rate - German import prices index - Weighted wholesale price index from 7 OEDD-countries - Capacity utilization - Unemployment rate

Register of tables in Histat - German monetary policy in the Bretton Woods era

The inflation rate in the United States declined significantly between June 2022 and January 2025, despite rising inflationary pressures towards the end of 2024. The peak inflation rate was recorded in June 2022, at 9.1 percent. In August 2023, the Federal Reserve's interest rate hit its highest level during the observed period, at 5.33 percent, and remained unchanged until September 2024, when the Federal Reserve implemented its first rate cut since September 2021. By January 2025, the rate dropped to 4.33 percent, signalling a shift in monetary policy. What is the Federal Reserve interest rate? The Federal Reserve interest rate, or the federal funds rate, is the rate at which banks and credit unions lend to and borrow from each other. It is one of the Federal Reserve's key tools for maintaining strong employment rates, stable prices, and reasonable interest rates. The rate is determined by the Federal Reserve and adjusted eight times a year, though it can be changed through emergency meetings during times of crisis. The Fed doesn't directly control the interest rate but sets a target rate. It then uses open market operations to influence rates toward this target. Ways of measuring inflation Inflation is typically measured using several methods, with the most common being the Consumer Price Index (CPI). The CPI tracks the price of a fixed basket of goods and services over time, providing a measure of the price changes consumers face. At the end of 2023, the CPI in the United States was 158.11 percent, up from 153.12 a year earlier. A more business-focused measure is the producer price index (PPI), which represents the costs of firms.

This paper studies the effects of a conventional monetary policy shock in the USA during times of high financial stress. The analysis is carried out by introducing a smooth transition factor model where the transition between states (?normal? and high financial stress) depends on a financial conditions index. Employing a quarterly dataset over the period 1970:Q1 to 2008:Q4 containing 108 US macroeconomic and financial time series, I find that a monetary policy shock during periods of high financial stress has stronger and more persistent effects on macroeconomic variables such as output, consumption and investment than it has during normal times. Differences in effects among the regimes seem to originate from nonlinearities in both components of the credit channel, i.e. the balance sheet channel and the bank-lending channel.

United States agriculture is a success story of high productivity growth maintained over a long period of time. Nevertheless, the industry today suffers from the same problems it has always suffered from: droughts, locusts, and market disruptions. In this article, the authors explain how monetary policy can contribute to a healthy agriculture sector. The reality is that the fundamental economic forces controlling the destiny of agriculture -- high productivity growth, the hazards of nature, the low price and income elasticities of demand, and the instability of conditions in important export markets -- are things that the Federal Reserve Board can do nothing about. The main message is that the best the Fed can do to stabilize the agricultural sector is to maintain low and steady inflation.

The Federal Reserve's balance sheet ballooned following its announcement to carry out quantitative easing to increase the liquidity of U.S. banks in early 2020. The balance sheet continued to grow in the following period as well, with a downward trend in 2023. As of February 29, 2024, the Fed's balance sheet amounted to roughly 7.6 trillion U.S. dollars. The most drastic increase in the observed period took place in the first half of 2020. This measure was taken to increase the money supply and stimulate economic growth in the wake of the damage caused by the COVID-19 pandemic. The Federal Reserve was not the only institution that implemented an expansionary monetary policy in response to the pandemic. For instance, the European Central Bank expanded its money supply in March 2020 and kept doing so over the following months. How do central banks increase the amount of money in circulation? Central banks can increase the money circulating in the economy in many ways. For instance, they can decrease banks’ reserve requirements to stimulate lending or decrease the interest rates to reduce the cost of borrowing for commercial banks. Alternatively, central banks can engage in open market operations (OMO) and buy securities such as government bonds from commercial banks or institutions. By conducting open market operations, the Federal Reserve expanded its balance sheet by seven trillion U.S. dollars between 2007 and 2023. All these measures aim to increase bank loans to entrepreneurs and consumers in order to stimulate employment and economic growth. Impact of COVID-19 on the U.S. economy The COVID-19 pandemic had a tremendous impact on national economies worldwide, and the United States was no exception. During the early months of the crisis, many lost their jobs, mostly those in lower-income categories. As a consequence, many Americans found it difficult to pay their rent and cover basic household expenses. Furthermore, in April 2022, most small business owners claimed that the pandemic had a large or moderate negative effect on their businesses. Overall, the gross domestic product (GDP) of the United States decreased by roughly 2.2 percent in 2020. In the following years, however, it increased notably, surpassing 25 trillion U.S. dollars in 2022.

Historical dataset of the daily level of the federal funds rate back to 1954. The fed funds rate is the interest rate at which depository institutions (banks and credit unions) lend reserve balances to other depository institutions overnight, on an uncollateralized basis. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate.

From 2003 to 2025, the central banks of the United States, United Kingdom, and European Union exhibited remarkably similar interest rate patterns, reflecting shared global economic conditions. In the early 2000s, rates were initially low to stimulate growth, then increased as economies showed signs of overheating prior to 2008. The financial crisis that year prompted sharp rate cuts to near-zero levels, which persisted for an extended period to support economic recovery. The COVID-19 pandemic in 2020 led to further rate reductions to historic lows, aiming to mitigate economic fallout. However, surging inflation in 2022 triggered a dramatic policy shift, with the Federal Reserve, Bank of England, and European Central Bank significantly raising rates to curb price pressures. As inflation stabilized in late 2023 and early 2024, the ECB and Bank of England initiated rate cuts by mid-2024, and the Federal Reserve also implemented its first cut in three years, with forecasts suggesting a gradual decrease in all major interest rates between 2025 and 2026. Divergent approaches within the European Union While the ECB sets a benchmark rate for the Eurozone, individual EU countries have adopted diverse strategies to address their unique economic circumstances. For instance, Hungary set the highest rate in the EU at 13 percent in September 2023, gradually reducing it to 6.5 percent by October 2024. In contrast, Sweden implemented more aggressive cuts, lowering its rate to 2.25 percent by February 2025, the lowest among EU members. These variations highlight the complex economic landscape that European central banks must navigate, balancing inflation control with economic growth support. Global context and future outlook The interest rate changes in major economies have had far-reaching effects on global financial markets. Government bond yields, for example, reflect these policy shifts and investor sentiment. As of June 2024, the United States had the highest 10-year government bond yield among developed economies at 4.09 percent, while Switzerland had the lowest at 0.69 percent. These rates serve as important benchmarks for borrowing costs and economic expectations worldwide.

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

National Coverage

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Triennial

Sampling procedure

As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.

Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or is the customary methodology. In most economies the fieldwork is completed in two to four weeks. In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size in United States was 1,021 individuals.

Mode of data collection

Other [oth]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.

The Volcker Shock was a period of historically high interest rates precipitated by Federal Reserve Chairperson Paul Volcker's decision to raise the central bank's key interest rate, the Fed funds effective rate, during the first three years of his term. Volcker was appointed chairperson of the Fed in August 1979 by President Jimmy Carter, as replacement for William Miller, who Carter had made his treasury secretary. Volcker was one of the most hawkish (supportive of tighter monetary policy to stem inflation) members of the Federal Reserve's committee, and quickly set about changing the course of monetary policy in the U.S. in order to quell inflation. The Volcker Shock is remembered for bringing an end to over a decade of high inflation in the United States, prompting a deep recession and high unemployment, and for spurring on debt defaults among developing countries in Latin America who had borrowed in U.S. dollars.

Monetary tightening and the recessions of the early '80s

Beginning in October 1979, Volcker's Fed tightened monetary policy by raising interest rates. This decision had the effect of depressing demand and slowing down the U.S. economy, as credit became more expensive for households and businesses. The Fed funds rate, the key overnight rate at which banks lend their excess reserves to each other, rose as high as 17.6 percent in early 1980. The rate was allowed to fall back below 10 percent following this first peak, however, due to worries that inflation was not falling fast enough, a second cycle of monetary tightening was embarked upon starting in August of 1980. The rate would reach its all-time peak in June of 1981, at 19.1 percent. The second recession sparked by these hikes was far deeper than the 1980 recession, with unemployment peaking at 10.8 percent in December 1980, the highest level since The Great Depression. This recession would drive inflation to a low point during Volcker's terms of 2.5 percent in August 1983.

The legacy of the Volcker Shock

By the end of Volcker's terms as Fed Chair, inflation was at a manageable rate of around four percent, while unemployment had fallen under six percent, as the economy grew and business confidence returned. While supporters of Volcker's actions point to these numbers as proof of the efficacy of his actions, critics have claimed that there were less harmful ways that inflation could have been brought under control. The recessions of the early 1980s are cited as accelerating deindustrialization in the U.S., as manufacturing jobs lost in 'rust belt' states such as Michigan, Ohio, and Pennsylvania never returned during the years of recovery. The Volcker Shock was also a driving factor behind the Latin American debt crises of the 1980s, as governments in the region defaulted on debts which they had incurred in U.S. dollars. Debates about the validity of using interest rate hikes to get inflation under control have recently re-emerged due to the inflationary pressures facing the U.S. following the Coronavirus pandemic and the Federal Reserve's subsequent decision to embark on a course of monetary tightening.

Policy analysis with potentially misspecified dynamic stochastic general equilibrium (DSGE) models faces two challenges: estimation of parameters that are relevant for policy trade-offs, and treatment of the deviations from the cross-equation restrictions. Using post-1982 US data, we study the robustness of the policy prescriptions from a state-of-the-art DSGE model with respect to two approaches to model misspecification pursued in the recent literature: (i) adding shocks to the DSGE model and/or generalizing the processes followed by these shocks; and (ii) explicit modeling of deviations from cross-equation restrictions (DSGE-VAR). (JEL C51, E13, E43, E52, E58)

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

National coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for United States is 1007.

Mode of data collection

Landline and mobile telephone

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.