Beyond market feeling: 3 indicators we created for understanding better what is happening on the construction market

This post of mine appeared first on the EUROCONSTRUCT blog in mid-February and introduced one of our researches in Hungary. This research is about creating such aggregates from the data of individual construction projects which carry new, up-to-date information on the current performance of construction market segments. Since then, however, we have published our first findings for the EECFA member Romania as well. Most of the original text stands for Romania too, but there are some differences so these are included in brackets.

Thanks to The National Bank of England for the fan chart and Cosgrove Hall Films for Jamie and the Magic Torch

The regular fan-chart of The Bank of England’s GDP forecast is perfectly honest about the challenge we all face while putting together historical construction data and forecast. Uncertainty is there, not only on the right, but on the left of the dotted line as well, thanks to revisions. This post is focusing on how uncertainty surrounding the present and some months ahead in the future could be eased with aggregated construction project data. These are Hungarian and Romanian examples.

When it comes to construction market size expressed in value, the typical questions Statistical offices ask when they gather the information are

who invested into what (investment statistics)?

who built what (construction statistics)?

In both cases you have preliminary data and final data. Because of the trade-off between timeliness (freshness) and coverage (fullness) you have to live with limited information for a while. Final annual investment figures in Hungary become available t+10 months [in Romania it is t+18 month], while final annual construction figures are out t+9 months [in Romania it is t+12 months], where t is latest full year. Furthermore, the scope (depth) is also subject to change, segment level breakdown (office, hotel, health, road, railway etc.) is only available as part of the final data.

For all these reasons, Buildecon and Ebuild Romania (Romanian member of EECFA) have been aiming to find a third leg which helps understand the present and to some extent the future performance of the segments better. This research we carry out together with and ELTINGA is about

systematically processing construction project information databases for Hungary and Romania

The construction project database about Hungary and Romania is something similar to the service provided by Dokugroup for Austria, Germany and Switzerland, by Dodge for North-America or by Cordell for Australia and New Zealand.

All of these are market based services, providing information on project level to each (potential) stakeholder. Typically, they provide detailed information about past, ongoing and planned projects, covering not only the parameters of the projects, but also contact information. From our viewpoint, their most important feature is that

project databases are updated daily with incoming new information, so they are very-very timely.

Out of the database, our analysis focuses only on those projects which are currently (at any point in time) under construction or were under construction (completed) from 2000 on [in Romania from 2014 on]. And the parameters of each project we use are

  • Start date
  • (Planned) Finish date
  • Value (net construction cost)
  • Function (residential, hotel, office, retail, road, railway, etc.)
  • Type (new vs renovation)
  • Location

The algorithms we have created aggregate the data of individual projects to segment level indicators.

Visually, the indicators look like this:


The observed period can be a quarter, a half-year or a year. Since we create time series for all indicator types, they become comparable in time. And here it starts to become really interesting.

To see it in practice, let me show some parts of the latest

EBI Construction Activity Report – H2 2016

Free access to H2 2016 reports:

1. Activity-Start indicator e.g. shows that in H2 2016 construction works started in the case of 159 office projects. Besides, we show that the total expected construction value of these works was recorded to be more than HUF 60 billion in the second half, which is around 40% larger than the corresponding value in H2 2015. [In the Romania report all value data are in EUR]


2. So this Activity-Start indicator is about the projects where construction works began in a given period, in this example in H2 2016. The new and renovation split shows that 25 new and 134 renovation office projects were started and the corresponding value of these works were registered to be around HUF 40 billion and HUF 20 billion. New construction experienced a growth of almost 3 times in value, while there is a drop in started renovation works compared to H2 2015.


3. Beside Activity-Start indicator, which is a sort of forward looking indicator, we calculate Output, which is a coincident type indicator. It is about the amount spent on construction in a given period. In the current report we included the yearly figures for Output and we show that according to our records almost HUF 100 billion were invested into office construction (as total, but new and renovation are calculated separately as well) and that this represented a 9% growth in 2016 over the previous year.


4. For Output, we included time series as well into the report, splitting them to new and renovation. From nowcasting viewpoint, these time series are the most important, telling us how strong the connections are between historical figures of the statistical office and segment Outputs coming from project aggregation. (Top 5 ongoing projects from the database were also included for each segment.)


The segments examined in the report:

  • Residential
  • Non-residential total
    • Hotel buildings
    • Office buildings
    • Wholesale and retail trade buildings
    • Traffic and communication buildings
    • Industrial buildings and warehouses
    • Education buildings
    • Health buildings
    • Agricultural buildings
    • Other non-residential buildings
  • Building construction total
  • Civil engineering
    • Roads
    • Railways
    • Airports runways
    • Bridges, elevated highways, tunnels and subways
    • Harbors and waterways
    • Complex industrial, energy, water works
    • Public utilities
    • Other civil engineering
  • Total

The content of the report:

  1. Activity-Start 1 – Constructions Started – Countrywide
  2. Activity-Start 2 – Constructions Started – Regional
  3. Activity-Start 3 – Constructions Started – Countrywide – New | Renovation
  4. Output 1 – Amount Spent On Construction – Countrywide – New | Renovation | Total
  5. Output 2 – Amount Spent On Construction – Countrywide – Time Series
  6. Formation and interpretation of indicators – background information

Available languages: Local, English

So here we stand now with this research. We have segment level information within days after the latest observed period. This helps nowcast and foresight. But being as honest as The Bank of England, I must add that project databases are not exempt from revision either. New projects become known to have been started and project parameters become more accurate with time.

The extent of this revision was discovered thanks to this research. And it also has very important consequences. On the one hand, we are able to give feedback to the data owner where to improve project research. On the other, by understanding the nature and the probable directions of the revision, we learn more on how to incorporate the findings into forecast. Parallel to this, with continuously monitoring how revision affects the aggregates in time, we will be able to set an optimal compilation date, after which the aggregates only change insignificantly.

This optimal compilation date is currently under examination, but this new torch we have by aggregating construction projects is in any way a great help in a relatively dark room.

Additional thoughts: In the methodological section of the report more information is available on the classifications applied, on the coverage and on the possible queries available, among others. And here I would like to say thanks to Dávid and Gergely Répássy ( and Áron Horváth (ELTINGA) for the common work that has brought us to this point.

Compiled by Janos Gaspar (Buildecon – EECFA Research), you may reach me at

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