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Architects as Nowcasters of Housing Construction

Published online by Cambridge University Press:  26 March 2020

Mark J. Holmes ,
James Mitchell  and
Brian Silverstone
Mark J. Holmes*
Affiliation:
University of WaikatoHamiltonNew Zealand
James Mitchell*
Affiliation:
NIESRLondonUnited Kingdom
Brian Silverstone*
Affiliation:
University of Waikato and NZIER Research AssociateHamiltonNew Zealand
*
E-mail: holmesmj@waikato.ac.nz
E-mail: j.mitchell@niesr.ac.uk
E-mail: silver@mngt.waikato.ac.nz
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Abstract

For more than four decades, the New Zealand Institute of Economic Research (NZIER) has conducted a two-question, quarterly survey of architect forecasts of public and private sector construction expenditure. This qualitative survey is published one week after the end of each quarter and nine weeks ahead of the official quantitative data thereby giving architect opinion nowcasting status. This paper covers selected aspects of this unexplored series with particular reference to residential housing construction and the value-added information from architects as nowcasters. Specifically, we consider several qualitative-to-quantitative conversion methods, in-sample and out-of-sample performance, cyclical features and respondent dynamics. Although our work relates to architects — a sub-sector of the service industry — our results have a wider application to business survey questions using ordered qualitative responses.

Keywords

Nowcastingreal-timearchitectsqualitative-to-quantitative conversionbusiness surveyshousing constructionC83E37
Type
Articles
Information
National Institute Economic Review , Volume 210 , October 2009 , pp. 111 - 122
Copyright
Copyright © 2009 National Institute of Economic and Social Research

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References

Anderson, O. (1952), ‘The business test of the IFO-Institute for Economic Research, Munich, and its theoretical model’, Review of the International Statistical Institute, 20, pp. 1–17.CrossRefGoogle Scholar
Aylmer, C. and Gill, T. (2003), ‘Business surveys and economic activity’, Reserve Bank of Australia Research Discussion Paper 2003-02.Google Scholar
Baker, K. and Saltes, D. (2005), ‘Architecture billings as a leading indicator of construction’, Business Economics, 40, pp. 67–73.CrossRefGoogle Scholar
Balcombe, K. (1996), ‘The Carlson-Parkin method applied to New Zealand price expectations using QSBO survey data’, Economics Letters, 51, pp. 51–7.CrossRefGoogle Scholar
Carlson, J.A. and Parkin, M. (1975), ‘Inflation expectations’, Economica, 42, pp. 123–38.CrossRefGoogle Scholar
Cunningham, A.W.F. (1997), ‘Quantifying survey data’, Bank of England Quarterly Bulletin, 37, pp. 292–300.Google Scholar
Cunningham, A.W.F., Smith, R.J. and Weale, M.R. (1998), ‘Measurement errors and data estimation: the quantification of survey data’, in Begg, I. and Henry, S.G.B. (eds), Applied Economics and Public Policy, Cambridge, Cambridge University Press.Google Scholar
Deitz, R. and Steindel, C. (2005), ‘The predictive abilities of the New York Fed's Empire State Manufacturing Survey’, Federal Reserve Bank of New York Current Issues in Economics and Finance, 11, pp. 1–7.Google Scholar
Driver, C., Imai, K., Temple, P. and Urga, G. (2004), ‘The effect of uncertainty on UK investment authorisation: homogenous vs. heterogeneous estimators’, Empirical Economics, 29, pp. 115- 28.CrossRefGoogle Scholar
Driver, C. and Urga, G. (2004), ‘Transforming qualitative survey data: performance comparisons for the UK’, Oxford Bulletin of Economics and Statistics, 66, pp. 71–89.CrossRefGoogle Scholar
Ghent, A.C. and Owyang, M.T. (2009), ‘Is housing the business cycle? Evidence from U.S. cities’, Federal Reserve Bank of Kansas City Working Paper 2009-07.Google Scholar
Hall, S.G.B. and Mitchell, J. (2009), ‘Recent developments in density forecasting’, in Mills, T.C. and Patterson, K. (eds), Palgrave Handbook of Econometrics, Volume 2: Applied Econometrics, Basingstoke, Palgrave.CrossRefGoogle Scholar
Hamilton, J.D. (1989), ‘A new approach to the economic analysis of nonstationary time series and the business cycle’, Econometrica, 57, pp. 357–84.CrossRefGoogle Scholar
Harris, M., Owens, R.E. and Sarte, P-D.G (2004), ‘Using manufacturing surveys to assess economic conditions’, Federal Reserve Bank of Richmond Economic Quarterly, 90, pp. 65–92.Google Scholar
Larsen, J. and Newton-Smith, R. (2001), ‘Using surveys of investment intentions’, Bank of England Quarterly Bulletin, 41, pp. 189–94.Google Scholar
Leamer, E.E. (2007), ‘Housing is the business cycle’, in Housing, Housing Finance, and Monetary Policy, Kansas City, Federal Reserve Bank of Kansas City.CrossRefGoogle Scholar
Matheson, T.D., Mitchell, J. and Silverstone, B. (2009), ‘Nowcasting and predicting data revisions in real time using qualitative panel survey data’, Journal of Forecasting (forthcoming).CrossRefGoogle Scholar
Mitchell, J., Smith, R.J. and Weale, M.R. (2002), ‘Quantification of qualitative firm-level survey data’, Economic Journal, 112, pp. 117–35.CrossRefGoogle Scholar
-(2005), ‘Forecasting manufacturing output growth using firm-level survey data’, Manchester School, 73, pp. 479–99.Google Scholar
-(2006), ‘A Bayesian indicator of manufacturing output from qualitative business panel survey data’, NIESR Discussion Paper 261.Google Scholar
Nardo, M. (2003), ‘The quantification of qualitative survey data: a critical assessment’, Journal of Economic Surveys, 17, pp. 645- 68.CrossRefGoogle Scholar
Pesaran, M.H. (1984), ‘Expectations formation and macroeconomic modelling’, in Malgrange, P. and Muet, P. (eds), Contemporary Macro-economic Modelling, Oxford, Blackwell.Google Scholar
-(1987), The Limits to Rational Expectations, Oxford, Blackwell.Google Scholar
Pesaran, M.H. and Weale, M.R. (2006), ‘Survey expectations’, in Elliott, G., Granger, C.W.J. and Timmermann, A. (eds), Handbook of Economic Forecasting, Amsterdam, North-Holland.Google Scholar
Silverstone, B. (2000), ‘Respondent dynamics within the NZIER survey of business opinion: an introductory perspective’, University of Waikato Working Papers in Economics 3/00, downloadable from ftp://mngt.waikato.ac.nz/RePec/wai/econwp/0003.pdfGoogle Scholar
Theil, H. (1952), ‘On the time shape of economic microvariables and the Munich business test’, Review of the International Statistical Institute, 20, pp. 105–20.CrossRefGoogle Scholar