Economic Data Types
Nayra Waddles
You can get stock and geographic data in Excel. It's as easy as typing text into a cell, and converting it to the Stocks data type, or the Geography data type. These two data types are considered linked data types because they have a connection to an online data source. That connection allows you to bring back rich, interesting information that you can work with and refresh.
In the picture above, the cells with company names in column A contain the Stocks data type. You know this because they have this icon: . The Stocks data type is connected to an online source that contains more information. Columns B and C are extracting that information. Specifically, the values for price, and change in price are getting extracted from the Stocks data type in column A.
In this example, column A contains cells that have the Geography data type. The icon indicates this. This data type is connected to an online source that contains more information. Columns B and C are extracting that information. Specifically, the values for population, and gasoline price are getting extracted from the Geography data type in column A.
Type some text in cells. If you want stock information, type a ticker symbol, company name, or fund name into each cell. If you want geographic data, type a country, province, territory, or city name into each cell.
If Excel finds a match between the text in the cells, and our online sources, it will convert your text to either the Stocks data type or Geography data type. You'll know they're converted if they have this icon for stocks: and this icon for geography:
Select one or more cells with the data type, and the Insert Data button will appear. Click that button, and then click a field name to extract more information. For example, for stocks you might pick Price and for Geography you might pick Population.
Click the Insert Data button again to add more fields. If you're using a table, here's a tip: Type a field name in the header row. For example, type Change in the header row for stocks, and the change in price column will appear.
Whenever you want to get current data for your data types, right-click a cell with the linked data type and select Data Type > Refresh. That will refresh the cell you selected, plus any other cells that have that same data type.
Linked data types connect to an online data source. Once you convert text to a linked data type, an external data connection is established in the workbook. That way, if the data changes online, you can update it by refreshing it in Excel. To refresh the data, right-click a cell with the linked data type and select Data Type > Refresh. That will refresh the cell you selected, plus any other cells that have that same data type.
After you convert text into the Stocks or Geography data types, an icon will appear in the cell. Click the icon to see the card. The card reveals a list of fields and corresponding values. Depending on the data, there could be numerous field/value pairs that you can see and work with.
For example, in this picture the card for France is shown. Capital is one of the fields available for France. And Paris is the value for that field. Leader(s) is another field, and the leader names are the values.
It is also possible to write formulas that use the values from the Stocks or Geography data types. This can be helpful if your data is not in a table. For example, type =A2 and then Excel's AutoComplete menu will appear, showing you the available fields for "France." You can also type a "dot", for example: =A2. and that will show the menu as well. For more information, see How to write formulas that reference data types.
Every economist may come up with their own favorite economic indicator. For many, a country's GDP usually represents the best overall picture of a country's economic health. It combines the monetary value of every good and service produced in an economy for a certain period, and it considers household consumption, government purchases, and imports and exports.
Yes, inflation is a lagging indicator that is reported after a rise in prices has occurred. This type of economic indicator is helpful for government agencies to set public policy, as without this type of data, they would not know the direction of the economy. Therefore, while inflation and other lagging indicators are still useful to investors, they are especially critical for developing future policy responses.
An economy may be strong if it has a robust amount of economic activity and job growth. This is measured by low unemployment, steady inflation, increases to construction, positive consumer index readings, and increasing GDP.
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Background: The evidence base informing economic evaluation models is rarely derived from a single source. Researchers are typically expected to identify and combine available data to inform the estimation of model parameters for a particular decision problem. The absence of clear guidelines on what data can be used and how to effectively synthesize this evidence base under different scenarios inevitably leads to different approaches being used by different modelers.
Objectives: The aim of this article is to produce a taxonomy that can help modelers identify the most appropriate methods to use when synthesizing the available data for a given model parameter.
Methods: This article developed a taxonomy based on possible scenarios faced by the analyst when dealing with the available evidence. While mainly focusing on clinical effectiveness parameters, this article also discusses strategies relevant to other key input parameters in any economic model (i.e., disease natural history, resource use/costs, and preferences).
Results: The taxonomy categorizes the evidence base for health economic modeling according to whether 1) single or multiple data sources are available, 2) individual or aggregate data are available (or both), or 3) individual or multiple decision model parameters are to be estimated from the data. References to examples of the key methodological developments for each entry in the taxonomy together with citations to where such methods have been used in practice are provided throughout.
Conclusions: The use of the taxonomy developed in this article hopes to improve the quality of the synthesis of evidence informing decision models by bringing to the attention of health economics modelers recent methodological developments in this field.
An area's economic and social characteristics have significant effects on its development and need for various types of public programs. To provide policy-relevant information about diverse county conditions to policymakers, public officials, and researchers, ERS has developed a set of county-level typology codes that captures a range of economic and social characteristics.
The 2015 County Typology Codes classify all U.S. counties according to six mutually exclusive categories of economic dependence and six overlapping categories of policy-relevant themes. The economic dependence types include farming, mining, manufacturing, Federal/State government, recreation, and nonspecialized counties. The policy-relevant types include low education, low employment, persistent poverty, persistent child poverty, population loss, and retirement destination.
Economic indicators come in multiple groups or categories. Most economic indicators come with a specific schedule for release and can be helpful in the right circumstance. Here are the three important types of economic indicators that we can group most into.
GDP is a lagging indicator. It is one of the first indicators used to gauge the health of an economy. It represents economic production and growth, or the size of the economy. Measuring GDP can be complicated, but there are two basic ways to measure it.
In addition, the government and Federal Reserve have used federal stimulus money and other strategies to keep markets high in order to avoid public panic in the event of an economic crisis. Since the market is vulnerable to manipulation, a stock or index price is not necessarily an accurate reflection of its value.
Unemployment is a lagging indicator. The Bureau of Labor Statistics releases a monthly estimate of the cumulative number of jobs lost or created in the previous month, as well as a percentage figure that represents how many Americans are unemployed and actively looking for work.
This unemployment rate is determined through a monthly survey of 60,000 households. It estimates the proportion of Americans who were unemployed during the period when the survey was taken. The unemployment rate only reflects people who are unemployed and looking for work.
The non-farm payrolls represent the total number of workers employed by U.S. businesses, other than general government employees, workers in private households, employees of non-profit organizations that provide assistance to individuals and farm workers.
The number of jobs created or lost in a month is an indicator of economic health and can significantly impact the securities markets. When more businesses are hiring, it suggests that businesses are performing well. More hiring can also lead to predictions that more people will have more money to spend since more of them are employed.
If unemployment rates rise unexpectedly or decline less than expected, that can sometimes be associated with a drop in stock prices as it may suggest that employers cannot afford to hire as many people. Remember, how an economic indicator comes in relative to expectations is very important.
CPI is a lagging indicator, and the U.S. relies on it heavily as one of the best indicators of inflation. This is because changes in inflation can spur the Federal Reserve to make changes to its monetary policy.
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