Submitting InstitutionLondon Business School
Unit of AssessmentBusiness and Management Studies
Summary Impact TypeEconomic
Research Subject Area(s)
Mathematical Sciences: Statistics
Summary of the impact
Now-casting is the prediction of the present, the very near
future, and the very recent past. It has been developed within a research
programme led by Lucrezia Reichlin at LBS. It is relevant because key
economic statistics, particularly quarterly measures such as GDP, are
available only with a delay. Now-casting exploits information which is
published early and at higher frequencies than the target variable and
generates early estimates before the offb01cial fb01gures become
Now-casting has signifb01cant infb02uence and impact. The techniques
reported in this case study are in widespread use by central banks and
policy institutions. Furthermore, this research has achieved successful
commercial impact via Now-Casting Economics Limited.
Reichlin and her co-authors have provided a formal statistical framework
for the now-casting process described above. During the 2008-13 period (at
LBS) she developed and published the key research papers which underpin
the commercial now-casting implementation.
Reichlin has developed methods for reading, through the lens of a model,
the fb02ow of data releases in real time. A now-casting model involves the
monitoring of many data releases, the formation of expectations, and the
revision of the assessment of the state of the economy whenever
realisations diverge signifb01cantly from expectations. A model for
quarterly GDP or other key series uses a large and heterogeneous set of
"hard" and "soft" predictors; everything from unemployment statistics to
consumer surveys. The model uses all of the data that is monitored by
market participants plus any other potentially relevant series to extract
a signal about the state of the economy.
The estimation procedure exploits the strong co-movement of these data
series so that their behaviour can be captured by few factors. All
now-casting output series (reported to clients via Now-Casting Economics)
are generated by a dynamic factor model developed by Doz, Giannone, and
Reichlin and published in the Review of Economic Statistics (2012)
and the Journal of Econometrics (2011). This model copes with the
`curse of dimensionality' (large numbers of correlated series) as it
involves the estimation of only a limited number of parameters for a large
dataset. The model assigns weights to the series and optimally exploits
the dynamic relationships among them. The now-cast can be interpreted as
that component of GDP growth which is highly correlated with all of the
input data series. It disregards idiosyncratic information such as the
weather, but it captures common signals given by all macroeconomic data
releases including surveys.
The technical details are these. A factor model is written in the state
form and the Kalman fb01lter is used to solve problems of missing data due
to the non-synchronicity of data release and other problems. The
Doz-Giannone-Reichlin research shows convergence properties of the maximum
likelihood estimator for the factors and the Kalman fb01lter; it also
demonstrates robustness to model misspecifb01cation. It explains why the
techniques work for the "big data" empirical situation faced by the
now-caster. This research is a development of ideas in Forni, Giannone,
Lippi and Reichlin published in Econometric Theory (2009), as well
as other work by Reichlin's team.
The now-casting methodology incorporates comprehensive technical
solutions to varying publication lags ("jagged edged" data), to
mixed-frequency data, and to missing input data. The model allows the
computation of a joint forecast of predictors and the target series and,
at each release, the calculation of the surprise component of the
published data release (this is the "news"). The revision of the now-cast
of quarterly GDP growth can then be described as the product of the weight
of each series (estimated using historical data) and the news for each
release. This gives a transparent means of reading the fb02ow of data
The research described here and Reichlin's contributions are summarised
in two survey papers published in the Handbook of Econometrics of
Forecasting (2013) and in the Oxford Handbook of Economic
Forecasting (2011). The surveys are an essential component of the
research programme; they provide a conduit for the subsequent impact of
References to the research
"A quasi-maximum likelihood approach for large, approximate dynamic
factor models," Doz, Giannone, and Reichlin, Review of Economics and
Statistics 94(4), Nov. 2012, pp. 1014-1024.
doi:10.1162/REST a 00225
"A two-step estimator for large approximate dynamic factor models based
on Kalman fb01ltering." Doz, Giannone, and Reichlin, Journal of
Econometrics 164(1), Sep. 2011, pp. 188-205.
"Opening the black box: structural factor models with large cross
sections" Forni, Giannone, Lippi, and Reichlin, Econometric Theory
25(5), Oct. 2009, pp. 1319-1347.
"Nowcasting and the real time data fb02ow," Banbura, Giannone, Modugno,
and Reichlin, Handbook of Econometrics of Forecasting, v. 2A, ed.
by Elliott and Timmermann. Elsevier (2013).
ISBN: 9780444536839 (print)
and 9780444536846 (eBook)
"Nowcasting," Banbura, Giannone, and Reichlin, Ch. 7 of Oxford
Handbook of Economic Forecasting, ed. by Clements and Hendry. Oxford
University Press (2011).
Evidence of quality. The Review of Economics and Statistics
is the leading applied economics journal; the Journal of Econometrics
and Econometric Theory are top fb01eld journals in econometrics.
In the Combes-Linnemer ranking, these outlets are ranked at positions 8,
11, and 38. In the ESRC-RES benchmarking review of UK economics, these
three journals were rated as 4*, 4*, and 3*. The North Holland (Elsevier)
Handbook and Oxford Handbook are from established and prestigious
publishing houses. The research has been cited extensively.
Details of the impact
Context. Key statistics on the present state of the economy are
available with a delay, and so now-casting is directly relevant for anyone
who needs to act on those statistics. For example, the fb01rst offb01cial
estimates of quarterly Gross Domestic Product (GDP) in the UK and USA are
published approximately one month after the reference quarter; in the Euro
area the lag is 2-3 weeks longer.
Relevant research. The relevant fb01ndings is the entire
now-casting methodology developed in the underpinning research
publications. Thus the outputs that have impact are the statistic
modelling techniques and the automated implementation of the techniques.
Benefb01ciaries. Two key groups of benefb01ciaries are (a) central
banks and policy institutions; and (b) private enterprises, especially
hedge funds and investment banks.
Within category (a), most central banks and other fb01nancial
institutions around the world have now adopted the now-casting methodology
on a routine basis. Examples of these benefb01ciaries include: (i) the
Euro system of central banks; (ii) the International Monetary Fund (IMF);
(iii) the Reserve Bank of New Zealand; (iv) Norges Bank; (v) the French
treasury; and (vi) the Hong Kong Institute for Monetary Research. Members
of sub-category (i) include Deutsche Bundesbank, Banque de France,
Netherlands Central Bank, and the Central Bank of Ireland.
Within category (b), private clients, particularly hedge funds,
extensively use web-based automated now-casting services provided via the
research-derived now-casting model.
Nature and process of the impact on category (a). In policy
institutions from category (a), including central banks, it is important
to have a timely view of the state of the economy. The now-casting
methodology helps them to update in real time and analyze a large quantity
of data in a coherent way. This is a step forward with respect to
judgemental procedures. The benefb01ciaries directly use the methodology
developed by the underpinning research. This process has been facilitated
by the publication and dissemination of those methods via the handbook
chapter surveys documented in the list of underpinning research. It also
facilitated by the direct involvement of Reichlin with these institutions;
for example, on the research advisory committee for the Norges Bank.
Nature and process of the impact on category (b). Turning to
category (b), private clients often lack the direct expertise to employ
directly the now-casting methods which are reported in the underpinning
research. To enable the wider impact of the research, Reichlin and her
collaborators founded a commercial venture. This is central to this impact
Now-Casting Economics Limited (see www.now-casting.com/about-us)
is based upon the underpinning research of Reichlin and her team. It
publishes automated "now-casts" of current quarter GDP growth in major
economies (USA, Japan, China, the Euro Area, Germany, France, Italy,
Spain, UK, and Canada) in real time. This service is built upon the
state-of-the-art econometric models from the underpinning research. It
gives professional investors and others a snapshot of "where we are today"
and a transparent framework for reading the fb02ow of economic news.
Extensive back-testing analysis shows that, for assessing current quarter
GDP, Now-Casting Economics is at least as accurate as the best
professional forecasters, but signifb01cantly more timely. Signifb01cant
changes in the macroeconomic environment are picked up earlier. Clients
can see the impact that every relevant data release has on GDP—again, in
real time. Subscribers also have access to a history of input data series
and to the continually revised GDP now-cast, via graphs, calendars, and
pages of detail on specifb01c data releases.
Now-Casting Economics is successful. It supports a team of six
contributing researchers and operators, and has built up a large portfolio
of clients. Clear evidence of impact is provided by the fact that such
clients pay signifb01cant fees for automated now-casts. Private commercial
details are not included here, but are available via the supplementary
"sources to corroborate the impact."
Sources to corroborate the impact
(a) Central banks and policy institutions have made extensive use of the
now-casting methodology. Working papers and offb01cial reports from all of
the institutions mentioned refer to Reichlin's work. The REF evaluators
are also welcome to contact directly key central bank and policy
institution personnel to verify the active use of the underpinning
research described in this case study. The supplemental corroboration
sources include specifb01c named personnel at the International Monetary
Fund, the European Central Bank, and the Federal Reserve. They are able to
confb01rm that the underpinning research reported here is directly used in
gives tabular and graphical illustrations of the fb01nal product available
to subscribers. A demonstration username and password for an account on
the Now-Casting is available for auditing purposes. The Now-Casting team
can also verify the scale of operations, describe the profb01le of the
client base, and report key fb01nancial indicators. Contact details for
these corroboration methods are contained with the supplement to this
Now-Casting Economics and its impact have also been reported in the
- Articles in the Financial Times by Ralph Atkins: "`Virtual
standstill' forecast for EU growth" 15 September 2011; "German slowdown
likely to lead to eurozone recession" 7 November 2011; "Sharp fall in
eurozone industrial output" 14 November 2011.
- Forecasts from Now-Casting Economics and communicated by the Economist
newspaper; see www.economist.com/blogs/freeexchange/2012/11/business-cycles.
- The now-casting research and the work of Now-Casting Economics have
achieved popular impact via TEDx: www.tedxwarwick.com/talks/talk.php?year=2013&id=8