Statistics New Zealand has only recently completed new estimates ofnational productivity for the economy. The new figures refer to what Statistics calls the “measured sector” of the economy. This definition excludes some industry sectors and local and central government and is said to be more representative of the commercial sector. The new estimates run from 1987/88 to 2004/05 and it has been stated that they will be extended backwards as time and resources permit. Statistics employs the Australian and New Zealand Standard Industrial Classification (ANZSIC). This system contains 117 separate categories and is known as ANZIND. The published statistics on GDP are aggregated to 30 industry categories. In Philpott's time, the published system included 22 industry categories.
Bryan Philpott last contributed to this subject in 1999 with the publication of data sets for real gdp, labour employed and real gross capital stock for the period 1960-1990 (Philpott 1994, 1999). His data is all converted to 1982/83 prices and is based on the then official data collections. In 2005 I updated the Philpott data base to the year 2002 with the help of official sources and arranged for the data set to be placed on the Motu website. This data set is
consistent with the earlier New Zealand Standard Industrial Classification (NZSIC).
Philpott Sources and DefinitionsReal Gross Domestic Product by SNA Industry Group: Professor Philpott utilised the existing Statistics data sets for GDP. Statistics moved the price base sucessively from 1982/83 to 1991/92 and then 1995/96 over the period under review. It is not clear how Philpott converted the later price based data to the earlier one. Between 1991/92 and 1995/96, Statistics changed from the New Zealand Standard Industrial Classification (NZSIC) to the Australia and New
Zealand Standard Industrial Classification (ANZSIC). This change of industry definitions meant changes in the grouping of the 117 base categories in the published 30 industry tables. In some published documents Statistics utilises a 52 industry breakdown. For updating
of NZSIC tables prepared before 1995/96, a system is needed to re-group the ANZSIC industries into the 22 industry categories employed by Philpott.There are 3 steps to generate NZSIC consistent records from present-day ANZSIC based statistical series:
Identify changes in the major industry groups;
Identify numerical changes as a result of re-classification; and
Adapt ANZSIC data sets to Philpott's NZSIC data sets.
Industry Groups: In most published tables there are 30
industry categories which Statistics labels ‘ANZSIC published
aggregates’ (Statistics 2004). In working papers Statistics
recognises a 52 industry table called ‘ANZIND published industry’
and a 117 industry classification called ‘ANZIND working industry’.
A comparison of the 30 industry list for ANZSIC and the 22 industry
list used by Philpott is shown in Box 1. In some cases, the
components within an ANZSIC 30 industry grouping have been changed
(e.g. Wood and Paper are brought together) and in some
cases an ANZSIC industry is published separately from its previous
grouping (e.g. Wholesale Trade).
|Forestry & Logging||Unchanged|
|Food, Beveridges, and Tobacco Manufacturing||Unchanged|
|Textiles & Apparel Manufacturing||Textiles, Apparel & Leather|
|Wood & Paper Product Manufacturing||Wood & Wood Products|
|Printing, Publishing & Recorded Media, Manufacturing||Paper Products, Printing & Publishing, Rubber & Plastics|
|Non-Metallic Mineral Product Manufacturing||Unchanged|
|Metal Product Manufacturing, Machinery & Equipment Manufacturing, Furniture & Other Manufacturing||Machinery, Metal Products & Other|
|Electricity, Gas & Water Supply||Unchanged|
|Wholesale Trade, Retail Trade, Accommodation, Restaurants & Bars||Trade, Restaurants & Hotels|
|Transport & Storage||Unchanged|
|Finance & Insurance, Property & Business Services||Finance & Insurance & Real Estate & Business Services|
|Ownership of Owner-Occupied Dwellings||Unchanged|
|Central Government, Local Government||Government, Central & Local & Health/Education|
|Personal and Community Services, Health & Education||Community, Social & Personal|
Numerical and other changes : David Haugh (2001) first worked
on this problem in The Treasury. He utilised the 1987-88 52-industry
nominal GDP tables to work out the implications for each industry
sector of the ANZSIC re-classification for comparisons with earlier
classifications. ANZSIC re-grouped each of the Wood, Paper,
and Machinery components of NZSIC with the weights shown in
Box 2. Our procedure requires us to transfer the components back to
their NZSIC equivalents. For Government and Personal
Services there were significant differences. Local Government
remained unchanged, but the education and health components of
Central Government were moved into Personal Services..
Box 2: Concordance Factors for Real GDP in 1987-88
Transfer 30% of combined total of ANZSIC Wood and Paper Products
and Furniture& Other to Machinery, Metal Products& Other
(representing Furniture) (balance combines with balance of
Wood& Paper Products to form Wood& Wood Product
Transfer 52% of ANZSIC Wood& Paper Products (representing
Wood Products) to Wood& Wood Products (balance to Paper
Products & Printing).
Transfer 30% of ANZSIC Metal Products Manufacture (representing
Basic Metal Manufacturing) to Basic Metal Products
(balance is Machinery and Equipment).
Maintain Finance, Insurance, Property and Business Services
as an aggregate
Transfer 34% of ANZSIC combined total of Government (Central and
Local) and Personal & Community to NZSIC Central
Government (balance to NZSIC Community & Personal
All other industries assumed to be defined approximately the same in
This procedure assumes that the concordance ratios hold constant
back through time. The Philpott series go back to 1960. By taking
1987-88 52-industry estimates the adjustment preserves any trend
shown in the Philpott data between the classification change, but the
absolute amounts would be increasingly distorted for the industries
concerned the further the series is extended back. An alternative
would be to weld the Philpott data to the ANZSIC data base by
matching the old data to the new data at a common year. This would
preserve the trend in the old data but the absolutes would still have
less meaning compared with the ANZSIC-Haugh framework.
NZSIC consistent Estimates: The third step is to extend the
Philpott tables from 1990 to 2002 by converting all GDP series
published since 1990 from an ANZSIC basis to an NZSIC basis using the
concordances in Box 2.
Measured Sector: The Statistics productivity aggregates are
confined to the productive sectors of the economy and are called the
‘measured sector’.The measured sector of the economy excludes from
the 30 industry table the following sectors: Property&Business
Services, Ownership of Owner-occupied Dwellings, Central
Government&Defence, Local Government Administration, and Personal
and Community Services. ‘Property and business services’
is not identified in the Philpott tables and in what follows it is
still included in the measured sector under Finance, Insurance and
Employment in Full Time Equivalents by Industry Group: This
data was first obtained from the Quarterly Employment Survey and from
1990 the Household Labour Force survey (HLFS). Part-time workers were
converted to full-time equivalent at a ratio of 0.35. This ratio was
chosen by Professor Philpott from data in the Quarterly Employment
Survey and relates to the then assumption part-time work was less
than 20 hours per week (Philpott 1992). Statistics New Zealand
curently employs a weighting of 0.5 and the requirement is less than
30 hours per week. For the present updating, Statistics provided a
special run from the HLFS with a weight of 0.35. The measured sector
FTEs are derived from the same categories as for GDP.
Gross Capital Stock: Philpott derived this series from
original sources. He established base stocks from the old Factory
Production Statistics from the 1950s. He then used Statisticsâ€™
capital expenditure series to update the stocks using the perpetual
inventory model (PIM). He assumed a lifetime for each class of
capital goods and depreciated each annual stock by a straight line
factor. (In a net capital stock series he used Inland Revenue
depreciation rates instead). From 1990 there was a delay in the
publication of industry capital expenditure and Philpott derived his
data from estimates given at the time by NZIER. In updating this
series, I took the latest Statistics capital formation series,
deflated it by the capital goods price index back to 1990 in 1982/83
prices, and re-estimated the gross stocks from the existing stock in
the Philpott series from 1990 onwards. Since then Statistics have
published their own estimates of productive capital stocks. While
these are based on the perpetual inventory method, they use different
assumptions for depreciation and capital gains. The measured sector
gross capital stock is derived by the same rules as for GDP.
Compensation of Employees by Industry Group: This is needed
for weighting the relative shares of capital and labour in the
multi-factor productivity index. Nominal GDP is divided between the
reward to capital and labour by identifying ‘compensation of
employees’ and the remainder (representing the reward to capital)
from national income statistics. This data is available in Philpott
(1994) up to 1991, and thereafter can be found in the national income
The weighted index for total factor inputs is obtained by weighting
the physical indexes of the two variables by a moving geometric
average of the annual factor shares (the Tornqvist formula). For the
measured sector, the labour share is slightly lower than that for the
economy as a whole. There is no reason to believe that the factor
shares for each year would differ between Philpottâ€™s data set and
those employed by Statistics New Zealand.
Statistics New Zealand Definitions:
Labour: ‘Estimates of labour volume are based upon hours
paid for all employed persons engaged in the production of goods and
services in the measured sector. The key data sources are the annual
Business Demography employee count, the Quarterly Employment Survey,
the five-yearly Population Census and the Household Labour Force
Survey. These sources are used to derive industry March-year annual
total hours paid series. These are then aggregated by a chained
Tornqvist index in which the weights are based on industry shares
of the measured sector nominal labour income (including
self-employed). Assuming a positive correlation between relative
industry labour incomes and skill levels, this industry weighting
regime implicitly goes some way towards quality-adjusting the labour
input series’(Statistics New Zealand 2006).
Capital Stocks: ‘The capital series takes as its starting
point the annual constant-price productive capital stocks series,
which have been developed using a perpetual inventory model that
generates productive stock estimates for 26 asset types by industry.
In addition to the PIM-derived fixed asset stocks, the range of
capital included in the productivity measures is supplemented by
separate estimates for three other assets, namely livestock, exotic
timber grown for felling and land in use in agriculture and
forestry. The productive capital stock represents the gross capital
stock (value of assets in existance) adjusted for efficiency loss. Capital service flows are assumed to be proportional to these
productive stock estimates, and are aggregated to the industry level
using a Tornqvist index with weights based upon implicit rental
prices (or user costs) which are a function of an endogenous rate of
return, depreciation and asset price changes. The measured sector
capital index is calculated, in turn, as a Tornqvist index of the
industry indexes, with the industry shares of total user costs
(equal to industry gross operating surplus less the estimated labour
income of the self-employed) providing the weights’ (ibid).
Composite input index: ‘A composite input index is
constructed by combining the labour and capital factor indexes at
the measured sector level. The total inputs index is a Tornqvist
index, with the factor shares of value-added providing the weights’
Comparisions of Productivity Parameters
Statistics (2006) presents productivity estimates for three periods: 1988-93,
1993-05 and 1988-05. As the Philpott tables have only been updated to
2002, the comparable periods have been estimated from the Statistics
data file in Table 1 (Jason Ede, Statistics, pers. com.).
Table 1:Average Annual Growth Rates for Productivity Parameters
Measured Sector by Periods in Philpott Data Set
(Stats estimates in parenthesis)
|1999-93||-2.6 (-3.2)||1.4 (2.0)||-0.3 (-0.2)||2.3 (3.2)||0.15 (1.2)|
|1993-02||2.1 (1.4)*||1.7 (2.4)||4.2 (4.1)||2.1 (2.6)||3.18 (2.2)|
|1988-02||0.4 (-0.3)*||1.6 (2.3)||2.6 (2.5)||2.3 (2.8)||2.00 (1.8)|
* Stats estimates adjusted to 1993-02 and 1988-02
The GDP series are most comparable as they are drawn from essentially
the same source. The Philpott capital stock series appears to
systematically underestimate the growth of capital stocks compared
with the Statistics series. Though the Statistics productive capital
stock series has a wider coverage the capital formation component is
drawn from the same source. In these circumstances, the differences
in growth of stocks appear to lie in the different depreciation
assumptions employed. Philpott assumed a lifetime decline in
usefulness while Statistics employs a sophisticated measure of loss
The Philpott labour series appear to fall more slowly and rise
faster than the Statistics series. Statistics have greatly improved
their estimates of actual labour expended in terms of hours worked.
This series is to be preferred in future work once it is extended
back to 1972.
In the period covered by the statistics the measured sector
contributed on average 65 per cent of industry GDP and accounted for
69 per cent of total paid hours (ibid p.9). Comparisions of annual
average growth rates in FTEs in the total economy and the measured
sector in the Philpott data set were:
|Period||Total Economy||Measured Economy|
economy dropped employment faster after the 1989 slump and has
recovered more slowly after 1993. In comparision with hours worked,
the measured sector FTEs fell more slowly in the first period and
rose more quickly in the second period.
The overall result is that measured sector labour productivity is
higher in the Statistics estimates (principally due to the
definition of the employment series), and multi-factor productivity
in the Statistics estimates is higher in the first period but lower
in the second period.
Long-term rates of growth
Since Professor Philpottâ€™s data set is the only comparable data set
to the recent Statistics estimates, his data is an excellent source
for estimates of long-term growth rates of the productivity
parameters for the measured sector (Table 2).
Table 2: Long-term Annual Average Growth Rates for
Productivity Parameters for Measured Sector by 10 Year Periods in
Philpott Data Set
* Tornqvist weighting for composite input index as in text.
theory terms, 1960-70 was a period of economic expansion with GDP
growth driven by high productivity growth and factor inputs. Lower
growth in 1970-80 was accompanied by lower productivity growth and in
labour employed in the measured sector. In 1980-90 productivity
continued to improve but employment fell. This combination
contributed to higher labour productivity. In 1990-2000 we have a
recovery in GDP growth (though not as good as the 1960s), through
good growth in MFP and both factor inputs.
Over the forty year period, GDP growth has been modest by
international standards at 2.76% per year, and growth of capital
employed has well exceeded labour employed. Capital per labour unit
has expanded considerably over the forty years as a result by a
factor of 2.36. We have sustained labour productivity increases of
over 2 per cent per year. Factor productivity throughout is in excess
of one per cent per year and helps maintain growth in national GDP of
2.76 per cent. Philpottâ€™s consistent assumption of 1 per cent per
year in a number of planning exercises has turned out to be an
underestimate. There is some suggestion that the growth of capital
stock has fallen in each sucessive 10 year period. This is not borne
out in the comparison of the 1988-93 and the 1993-02 periods in
Table 1. It remains a possibility for further investigation whether
MFP can increase without gains in capital productivity.
I believe that the new Statistics New Zealand estimates of national
productivity are an improvement on previous estimates of the
essential parameters. Their usefulness will be enhanced when the
series are extended back to 1972 as has been announced. In the
meantime, the data set assembled by Professor Bryan Philpott of
Victoria University back to 1960 is one of a few sources that is
sufficiently comprehensive and consistent to estimate long-term
trends in the national productivity parameters. On this evidence,
labour employed in productive activities is shown to fluctuate with
changes in the economic cycle while capital employed increased at a
faster rate in earlier decades than it did in later decades. The
drive for productivity growth appears to have slowed in the first two
decades but slowly recovered in the second two decades. More research
would be useful to determine the source of these changes.
Haugh, David (2001), Calibration of a Chain Linked Volume Production GDP Database,
Johnson R W M (2004), Making the ANZSIC work for Economics, NZ
Association of Economists, Wellington.
Johnson R W M (2002), OECD, Growth and Measurement: Philpott
Revisited, NZ Association of Economists, Wellington.
Philpott, B P (1992) A Consistent Data Base of Sectoral Employment, RPEP Occasional Paper 106, Victoria University of Wellington Research
Project on Economic Planning.
Philpott B P (1994), Data Base of Nominal and Real Output, Labour,
and Capital Employed by SNA Industry Group 1960-1990, RPEP Paper
265, Victoria University.
Philpott B P (1999), Provisional Estimates for 1990-98 of Output
Labour & Capital Employed by SNA Industry Group, RPEP Paper
293, Victoria University.
Statistics New Zealand (2004), ANZIND Hierarchy, Technical
Support Services (pers com).
Statistics New Zealand (2006), Productivity Statistics: 1988-2005, Productivity Information Paper 1988-2005