How do you adjust for economic data?

Economic data can be useful for understanding the state and trends of different markets, sectors, and indicators. However, raw data may not always reflect the true picture, as they can be affected by various factors such as inflation, seasonality, population changes, and measurement errors. Therefore, economists often adjust or transform economic data to make them more comparable, consistent, and meaningful. In this article, you will learn how to adjust for economic data using some common methods and tools.

1 Nominal vs. Real

One of the most basic adjustments for economic data is to distinguish between nominal and real values. Nominal values are the current or face values of economic variables, such as prices, wages, and GDP. Real values are the values adjusted for inflation, which means they reflect the purchasing power of money over time. To calculate real values, you need to use a price index, such as the Consumer Price Index (CPI), that measures the changes in the average level of prices. The formula for converting nominal values to real values is: Real value = Nominal value / Price index

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Jose Bueno

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In economics, nominal value is measured in terms of money, while real value or price is measured against goods or services. A real value is one that has been adjusted for inflation, allowing comparison of quantities as if the prices of goods had not changed on average. Therefore, value changes in real terms exclude the effect of inflation. Unlike a real value, a nominal value has not been adjusted for inflation, so changes in the nominal value reflect, at least in part, the effect of inflation. The face value of a commodity package tends to change over time. On the contrary, by definition, the real value of the basket of commodities as a whole remains the same over time.

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2 Seasonal Adjustment

Another common adjustment for economic data is to remove the effects of seasonal patterns, such as holidays, weather, and school calendars, that can cause fluctuations in the data. Seasonal adjustment aims to isolate the underlying trend and cyclical movements of the data, making them easier to analyze and forecast. To perform seasonal adjustment, you need to use a statistical method, such as the X-13ARIMA-SEATS method, that estimates and removes the seasonal component from the data. Many official sources, such as the Bureau of Economic Analysis (BEA) and the Bureau of Labor Statistics (BLS), provide seasonally adjusted data for various indicators.

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Jose Bueno

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The real values of individual goods or commodities may rise or fall against each other, relatively speaking, but a representative bundle of commodities as a whole retains its real value as a constant from one period to the next. Real wages and real gross domestic products The package of goods used to measure the Consumer Price Index (CPI) is applicable to consumers. So, for wage earners as consumers, an appropriate way to measure real wages (the purchasing power of wages) is to divide the nominal wage (after taxes) by the CPI growth factor.

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Expedito 🎗️⚖️🎗️ Teixeira de Carvalho Filho . ' .

Advogado Criminalista | Mestrado em Sistemas Integrados de Gestão
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Common sense is needed in every aspects of macroeconomics…🤔 But, nonetheless, nothing is more useful for analysts than several commonly used adjustment methods: 1. - estimation by ratio; 2. - regression estimation; 3. - post-stratiﬁ ed estimation, and much more… computers and the statistics science are there to help us…🤔

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3 Per Capita Adjustment

A third type of adjustment for economic data is to account for the size and growth of the population. Per capita adjustment means dividing the total or aggregate value of an economic variable by the population, resulting in an average or per person value. This adjustment can help compare the economic performance and well-being of different countries or regions, as well as the changes over time. To calculate per capita values, you need to use reliable and consistent data on population, such as the Census Bureau or the World Bank.

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Jose Bueno

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Gross domestic product (GDP) is a measure of aggregate production. Nominal GDP in a particular period reflects the prices prevailing at that time, while real GDP compensates for inflation. U.S. price indices and national product and income accounts are constructed from bundles of commodities and their respective prices. In the case of GDP, an appropriate price index is the GDP price index. In the US National Income and Product Accounts, nominal GDP is called GDP in current dollars (that is, in current prices for each designated year), and real GDP is called GDP in [base year] dollars. (that is, in dollars you can buy the same amount of commodities as in the base year). Education is the first step towards financial freedom: learn about FIN.

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4 Standardization and Indexation

A fourth way to adjust for economic data is to make them more comparable and relative by using standardization and indexation. Standardization means converting the data to a common unit or scale, such as percentages, ratios, or scores, that can eliminate the differences in magnitude and dimension. Indexation means expressing the data as a proportion or fraction of a base or reference value, such as 100, 1, or the average, that can show the changes and variations over time or across groups. To standardize or index the data, you need to use simple mathematical operations, such as division, multiplication, or subtraction.

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5 Data Quality Adjustment

A fifth and final adjustment for economic data is to improve their quality and accuracy by correcting or reducing the errors and biases that may arise from the data collection and processing methods. Data quality adjustment can involve various techniques, such as sampling, weighting, imputation, revision, and smoothing, that can address the issues of missing, incomplete, outdated, or noisy data. To apply data quality adjustment, you need to use appropriate and transparent methods, such as the American Community Survey (ACS) or the Current Population Survey (CPS), that can provide reliable and consistent data sources.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you adjust for economic data?

1

2

3

4

5

6

1 Nominal vs. Real

2 Seasonal Adjustment

3 Per Capita Adjustment

4 Standardization and Indexation

5 Data Quality Adjustment

6 Here’s what else to consider

Economics

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How do you adjust for economic data?

1

2

3

4

5

6

1 Nominal vs. Real

2 Seasonal Adjustment

3 Per Capita Adjustment

4 Standardization and Indexation

5 Data Quality Adjustment

6 Here’s what else to consider

Economics

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