DMPED is using economic data to drive positive change and build good government for District of Columbia residents. They are focusing on collecting and compiling information about the city, in particular on D.C.’s economic development priorities that create more pathways to the middle class: jobs, quality affordable housing, and community-focused development.This site is an online version of the Deputy Mayor for Planning and Economic Development’s weekly dashboard. This dashboard is also transmitted to the City Administrator, the Mayor, and other senior staff, so they can be aware of economic trends and context. It includes only data that is public, so certain indicators that DMPED uses are not included.

OVERVIEWStudents will use the Texas Counties Population and Agriculture Dashboard to answer TEKS specific questions. The exercise takes the student back in time as a rancher. They must fill out a bill of sale and read a small fictional letter from 1860. They must use their math skills and make predictions about how to proceed the following year. The questions they must answer come straight from the economics section of the 7th grade TEKS.LEARNING OBJECTIVESBy the end of this lesson, you will be able to…Discuss the impact of laws of supply and demand on the history of farming in Bexar County.Locate the mathematical mean for the number of animals slaughtered and use that information to make economic decisions.Discuss and make predictions about the growth of Bexar County.TEKS COVEREDSocial Studies: 1A, 9A, 10B, 12B, 19A, 20A, B, C, 21A, B, 22A, B, C Math: 6th Grade 1A, E, F, G, 3D, 5BMATERIALS NEEDED: • Laptop or computer with internet access • Pencil and Handout • Attached Job Aid

Sioux Falls Dashboard - Economic Indicators - Single Family Additions

The median age indicates the age separating the population group into two halves of equal size.

This app contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values. The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: March 2021 (preliminary values at the state and county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2019 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.To better understand the different labor force statistics included in this map, see the diagram below from BLS:Esri's U.S. Updated Demographic Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Data Note: The median household income value divides the distribution of household income into two equal parts. Pareto interpolation is used if the median falls in an income interval other than the first or last. For the lowest interval, <$10,000, linear interpolation is used. If the median falls in the upper income interval of $500,000+, it is represented by the value of $500,001. Additional Esri Resources:Esri DemographicsU.S. 2020/2025 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

This dashboard presents a set of annual financial indicators for the economy as a whole (‘total economy’) and for each institutional sector of the economy: non-financial corporations, financial corporations, general government, households and Non-Profit Institutions Serving Households (NPISH). It provides users with key indicators of the financial health of economies and their sectors. The indicators are calculated from the financial accounts (flows) and balance sheets (stocks), which are compiled in accordance with the 2008 System of National Accounts. The information buttons in the tables provide further details about each of the indicators, including definitions and formulas.

Hug page featuring Sioux Falls Dashboard - Economic Indicators - Finance - Unemployment Rate.

Hub page featuring Sioux Falls Dashboard - Economic Indicators - Multi-Family Projects.

Hub page featuring Sioux Falls Dashboard - Economic Indicators - Commercial Projects.

This dashboard presents a set of annual financial indicators for the economy as a whole (‘total economy’) and for each institutional sector of the economy: non-financial corporations, financial corporations, general government, households and Non-Profit Institutions Serving Households (NPISH). It provides users with key indicators of the financial health of economies and their sectors. The indicators are calculated from the financial accounts (flows) and balance sheets (stocks), which are compiled in accordance with the 2008 System of National Accounts. The information buttons in the tables provide further details about each of the indicators, including definitions and formulas.

For indicators of debt, the measure used is the broadest measure of debt which may include the following financial liabilities (although coverage varies by sector and by country): Special Drawing Rights, currency and deposits, debt securities (at market value), loans, insurance, pensions and standardised guarantees, and other accounts payable. The ‘adjusted’ measure of debt – as well as of net financial worth – excludes unfunded pension liabilities. As financial liability coverage varies between countries, users should proceed with caution when comparing different countries.

This table is on a consolidated basis, meaning that counterpart assets and liabilities of units within the same sector are removed. The exception is data for Chile, Colombia, Korea and Mexico which is on a non-consolidated basis, meaning that it shows all assets and liabilities of units in a sector without removing counterpart assets and liabilities of units within the same sector.

The data within this dashboard shows how we are performing against our objective to encourage and assist seniors, women and people with disability to participate in social and economic life by:

• supporting seniors to be healthy and active as they age

• reducing barriers to people with disability participating in daily life

• increasing the proportion of women on boards

• increasing the proportion of women in non-traditional trades.

The Economic Indictor Service (EIS) aims to deliver professional economic content to financial institutions on both the buy and sell side service providers. This service covers 136 countries and 43,000 recurring indicators, which are updated on a real-time basis.

We are currently adding additional indicators/countries from Africa as well as expanding our coverage of Indicators in G20. In addition, it provided data of over 1,700 non-recurring indicators in 2020.

The EIS service includes historic data on recurring economic indicators. Recurring events include GDP data, unemployment releases, PMI numbers etc. Information on economic indicators, includes details of issuing agency and historical data series is made available depending on its availability.

The two components available for the Economic Calendar are the following:

1. Live Calendar - updated 24/5 immediately after the data is released and with limited history for recurring indicators.

2. Historical Database - Database of all recurring indicators (with complete history) and non-recurring indicators

Live Calendar can be embedded on client's website using iFrame or API. Historical Database can be made available via API or FTP.

Additional Features of the Economic Indicator Service - Delivery of unique newsfeed by using algorithms and analysts - Feed to client’s website with customized branding - Automatic feed to social media accounts, such as: Twitter and Facebook - Desktop ticker updates - Mobile App integration - Bespoke dashboards for macro-economic & industry reports And most importantly, clients can customize filters to get the specific economic indicators (e.g. for specific countries) they need.

A good retail broker can gain advantage by minimizing the time lag in real time information flow to retail investors vis-à-vis institutional investors. One way to achieve this is by providing access to clients with timely and accurate access to all major economic and other market moving announcements / data. - In order to minimize this disadvantage, many broker dealers provide economic calendar and news flows on their trading platforms. - We have developed two distinct products – Economic Calendar and Economic News to meet this requirement.

Contact Ilze Gouws, i.gouws@africadata.com for more information.

Information on the main changes and historical trends for the main quarterly personal and economic well-being measures.

Hub page featuring Sioux Falls Dashboard - Economic Indicators - Finance - Rolling Average Sales Tax.

The financial indicators are based on data compiled according to the 2008 SNA "System of National Accounts, 2008". Many indicators are expressed as a percentage of Gross Domestic Product (GDP) or as a percentage of Gross Disposable Income (GDI) when referring to the Households and NPISHs sector. The definition of GDP and GDI are the following:

Gross Domestic Product:
Gross Domestic Product (GDP) is derived from the concept of value added. Gross value added is the difference of output and intermediate consumption. GDP is the sum of gross value added of all resident producer units plus that part (possibly the total) of taxes on products, less subsidies on products, that is not included in the valuation of output [System of National Accounts, 2008, par. 2.138]. GDP is also equal to the sum of final uses of goods and services (all uses except intermediate consumption) measured at purchasers’ prices, less the value of imports of goods and services [System of National Accounts, 2008, par. 2.139]. GDP is also equal to the sum of primary incomes distributed by producer units [System of National Accounts, 2008, par. 2.140].

Gross Disposable Income:
Gross Disposable Income (GDI) is equal to net disposable income which is the balancing item of the secondary distribution income account plus the consumption of fixed capital. The use of the Gross Disposable Income (GDI), rather than net disposable income, is preferable for analytical purposes because there are uncertainty and comparability problems with the calculation of consumption of fixed capital. GDI measures the income available to the total economy for final consumption and gross saving [System of National Accounts, 2008, par. 2.145].

Definition of Debt:
Debt is a commonly used concept, defined as a specific subset of liabilities identified according to the types of financial instruments included or excluded. Generally, debt is defined as all liabilities that require payment or payments of interest or principal by the debtor to the creditor at a date or dates in the future. Consequently, all debt instruments are liabilities, but some liabilities such as shares, equity and financial derivatives are not debt [System of National Accounts, 2008, par. 22.104]. According to the SNA, most debt instruments are valued at market prices. However, some countries do not apply this valuation, in particular for securities other than shares, except financial derivatives (AF33). In this dataset, for financial indicators referring to debt, the concept of debt is the one adopted by the SNA 2008 as well as by the International Monetary Fund in “Public Sector Debt Statistics – Guide for compilers and users” (Pre-publication draft, May 2011). Debt is thus obtained as the sum of the following liability categories, whenever available / applicable in the financial balance sheet of the institutional sector:special drawing rights (AF12), currency and deposits (AF2), debt securities (AF3), loans (AF4), insurance, pension, and standardised guarantees (AF6), and other accounts payable (AF8). This definition differs from the definition of debt applied under the Maastricht Treaty for European countries. First, gross debt according to the Maastricht definition excludes not only financial derivatives and employee stock options (AF7) and equity and investment fund shares (AF5) but also insurance pensions and standardised guarantees (AF6) and other accounts payable (AF8). Second, debt according to Maastricht definition is valued at nominal prices and not at market prices.

To view other related indicator datasets, please refer to:
Institutional Investors Indicators [add link]
Household Dashboard [add link]

A page displaying data on the economic impact of COVID-19 in Connecticut

This 6MB download is a zip file containing 5 pdf documents and 2 xlsx spreadsheets. Presentation on COVID-19 and the potential impacts on employment

May 2020Waka Kotahi wants to better understand the potential implications of the COVID-19 downturn on the land transport system, particularly the potential impacts on regional economies and communities.

To do this, in May 2020 Waka Kotahi commissioned Martin Jenkins and Infometrics to consider the potential impacts of COVID-19 on New Zealand’s economy and demographics, as these are two key drivers of transport demand. In addition to providing a scan of national and international COVID-19 trends, the research involved modelling the economic impacts of three of the Treasury’s COVID-19 scenarios, to a regional scale, to help us understand where the impacts might be greatest.

Waka Kotahi studied this modelling by comparing the percentage difference in employment forecasts from the Treasury’s three COVID-19 scenarios compared to the business as usual scenario.

The source tables from the modelling (Tables 1-40), and the percentage difference in employment forecasts (Tables 41-43), are available as spreadsheets.

Arataki - potential impacts of COVID-19 Final Report

Employment modelling - interactive dashboard

The modelling produced employment forecasts for each region and district over three time periods – 2021, 2025 and 2031. In May 2020, the forecasts for 2021 carried greater certainty as they reflected the impacts of current events, such as border restrictions, reduction in international visitors and students etc. The 2025 and 2031 forecasts were less certain because of the potential for significant shifts in the socio-economic situation over the intervening years. While these later forecasts were useful in helping to understand the relative scale and duration of potential COVID-19 related impacts around the country, they needed to be treated with care recognising the higher levels of uncertainty.

The May 2020 research suggested that the ‘slow recovery scenario’ (Treasury’s scenario 5) was the most likely due to continuing high levels of uncertainty regarding global efforts to manage the pandemic (and the duration and scale of the resulting economic downturn).

The updates to Arataki V2 were framed around the ‘Slower Recovery Scenario’, as that scenario remained the most closely aligned with the unfolding impacts of COVID-19 in New Zealand and globally at that time.

Find out more about Arataki, our 10-year plan for the land transport system

May 2021The May 2021 update to employment modelling used to inform Arataki Version 2 is now available. Employment modelling dashboard - updated 2021Arataki used the May 2020 information to compare how various regions and industries might be impacted by COVID-19. Almost a year later, it is clear that New Zealand fared better than forecast in May 2020.Waka Kotahi therefore commissioned an update to the projections through a high-level review of:the original projections for 2020/21 against performancethe implications of the most recent global (eg International monetary fund world economic Outlook) and national economic forecasts (eg Treasury half year economic and fiscal update)The treasury updated its scenarios in its December half year fiscal and economic update (HYEFU) and these new scenarios have been used for the revised projections.Considerable uncertainty remains about the potential scale and duration of the COVID-19 downturn, for example with regards to the duration of border restrictions, update of immunisation programmes. The updated analysis provides us with additional information regarding which sectors and parts of the country are likely to be most impacted. We continue to monitor the situation and keep up to date with other cross-Government scenario development and COVID-19 related work. The updated modelling has produced employment forecasts for each region and district over three time periods - 2022, 2025, 2031.The 2022 forecasts carry greater certainty as they reflect the impacts of current events. The 2025 and 2031 forecasts are less certain because of the potential for significant shifts over that time.

Data reuse caveats: as per license.

Additionally, please read / use this data in conjunction with the Infometrics and Martin Jenkins reports, to understand the uncertainties and assumptions involved in modelling the potential impacts of COVID-19.

COVID-19’s effect on industry and regional economic outcomes for NZ Transport Agency [PDF 620 KB]

Data quality statement: while the modelling undertaken is high quality, it represents two point-in-time analyses undertaken during a period of considerable uncertainty. This uncertainty comes from several factors relating to the COVID-19 pandemic, including:

a lack of clarity about the size of the global downturn and how quickly the international economy might recover differing views about the ability of the New Zealand economy to bounce back from the significant job losses that are occurring and how much of a structural change in the economy is required the possibility of a further wave of COVID-19 cases within New Zealand that might require a return to Alert Levels 3 or 4.

While high levels of uncertainty remain around the scale of impacts from the pandemic, particularly in coming years, the modelling is useful in indicating the direction of travel and the relative scale of impacts in different parts of the country.

Data quality caveats: as noted above, there is considerable uncertainty about the potential scale and duration of the COVID-19 downturn. Please treat the specific results of the modelling carefully, particularly in the forecasts to later years (2025, 2031), given the potential for significant shifts in New Zealand's socio-economic situation before then.

As such, please use the modelling results as a guide to the potential scale of the impacts of the downturn in different locations, rather than as a precise assessment of impacts over the coming decade.

New Brunswick Economic Dashboard

This data package includes the underlying data to replicate the charts and calculations presented in The International Economic Implications of a Second Trump Presidency, PIIE Working Paper 24-20.

If you use the data, please cite as:

McKibbin, Warwick, Megan Hogan, and Marcus Noland. 2024. The International Economic Implications of a Second Trump Presidency. PIIE Working Paper 24-20. Washington: Peterson Institute for International Economics.

This web map presents 2023 economic data for redevelopment at Superfund sites at a national level. EPA's Superfund Redevelopment Program, (SRP) tracks this information over time to give a general overview of the national beneficial effects associated with Superfund redevelopment. To date, SRP has tracked these benefits from 2011 through 2023. This web map was built to be used in the Redevelopment Economics at Superfund Sites dashboard for the Redevelopment Economics at Superfund Sites StoryMap. Contact bqboggs@skeo.com with any questions.