1. Integrated Data for Policy
A view from New Zealand
Lynda Sanderson
OECD Global Forum on Productivity Conference
Sydney, 20-21 June 2019

2. Integrated Firm Data in New Zealand
• Basic LEED data available since 2004
• LBD developed 2005-07. Available to researchers since
April 2007.
What is the LBD?
• A collection of longitudinal administrative and survey data
held by Statistics New Zealand
• Valued for research purposes because of its dimensionality
• Length: Tracks firms over time since April 1999
• Breadth: Basic info on all economically significant firms in NZ
• Depth: Substantial detail on specific groups of firms/activities

3. New Zealand’s Longitudinal Business Database
National
Accounts (AES)
Financial
summary (IR10)
GST returns (GST)
Company tax
returns (IR4)
Merchandise
trade (OMT)
LEED
EMS, IR4S
IR7, IR3
Intellectual
property (IPO)
Int’l Trade in
services (ITSS)
Int’l Investment
(QIIS/AIIS)
Agricultural
Production (APS)
Business
Operations (BOS)
Energy use
(NZEUS)
Govt assistance
(GAP)
R&D survey
Administrative data from IR
Other administrative data
Current StatsNZ surveys
One-off StatsNZ surveys
Individual-level data (IDI)
LongitudinalBusinessFrame
Current Non-StatsNZ surveys
Nat’l Employer
survey (NSE)
Accommodation
survey (CAM)
Substantial investment in
harmonised datasets for
labour and productivity
measurement.

4. Integrated Data in New Zealand
Longitudinal Business Database
Financial
summary (IR10)
GST returns (GST)
Company tax
returns (IR4)
Merchandise
trade (OMT)
Intellectual
property (IPO)
Int’l Trade in
services (ITSS)
Int’l Investment
(QIIS/AIIS)
Agricultural
Production (APS)
Business
Operations (BOS)
Energy use
(NZEUS)
Govt assistance
(GAP)
R&D survey
Health
Education
Migration
Administrative data from IR
Other administrative data
Current StatsNZ surveys
One-off StatsNZ surveys
Corrections
Benefits
.......
.......
Census 2013
Individual-level data (IDI)
LongitudinalBusinessFrame
IntegratedDataInfrastructureSpine
Current Non-StatsNZ surveys
Nat’l Employer
survey (NSE)
Accommodation
survey (CAM)
Integrated Data Infrastructure
IDI prototype
developed in 2011,
available 2012.
Currently links 49
data sets, with 20
more applications
received.
LEED
EMS, IR4S
IR7, IR3
National
Accounts (AES)

5. Accessing the data
• Huge progress since 2007
• Stats Act Amendment 2012: Access to anonymised
individual data can be provided to any person, subject to:
• Bona fide research in the public interest
• Appropriate skills and experience
• Tax Administration Act 1994: Core LBD data restricted to
government researchers
• Includes universities, CRIs, government agencies (broadly defined)
• Geographically limited: 32 remote datalabs, but only
accessible within New Zealand

6. What can we learn for policy?
Examples from Firm Internationalisation

7. Context: Internationalisation in New Zealand
• New Zealand is a highly internationalised society, but our
firms are not particularly internationally connected
• Successive governments have prioritised policies to enhance
international engagement
• An important, but polarised, policy issue

8. International Engagement – Key questions
Research:
• What impact does firm internationalisation have on the
outcomes that we care about?
• Internationalisation: flows of goods and services; capital; people;
ideas
• Outcomes: productivity, employment, wellbeing…
• What firm-level and environmental factors influence a firm’s
ability (and incentives) to internationalise?
• What does the current landscape look like?
Policy:
• How can government change the environment in order to
enhance the potential for positive outcomes and mitigate
unintended consequences?

9. Not just about aggregate outcomes
When looking at productivity impacts, we need to think about:
• Mechanisms
• learning, scale, capacity utilisation, investment incentives…
• Channels
• direct effects, resource reallocation, spillovers
• Heterogeneity
• different industries, population groups, partner countries…
• Other outcomes
• Important in their own right (eg, employment, working conditions)
• Potential flow-on effects to productivity (eg, innovation)

10. • In the absence of data, policy makers use stories.
• An appealing story:
Learning-by-exporting
Source: Fabling, Richard & Lynda Sanderson (2013) “Exporting and
performance: Market entry, investment and expansion”, Journal of
International Economics 89(2) pp.422-431
Challenging appealing but speculative narratives

11. Multidimensional, heterogeneous outcomes
What drives the foreign wage premium?
(a) Heterogeneous Workers: foreign firms select higher
quality workers
(b) Heterogeneous Firms: foreign firms pay more for a given
quality of worker
(c) Heterogeneous Learning: foreign firms provide greater
learning opportunities, resulting in higher wage growth
and/or
(d) Heterogeneous Sourcing: foreign firms bring in highly-paid
workers/managers from offshore
Source: Maré, David C, Lynda Sanderson and Richard Fabling (2014)
“Earnings and employment in foreign-owned firms” Treasury Working
Paper 14/16, New Zealand Treasury

12. But not that simple…
• Foreign premium tends to increase earnings inequality:
• Foreign firms not only tend to hire better workers, they also pay a
higher skill premium
• Earnings growth premium is positive only for males, significant only
for prime age
• Not clear that the skills obtained are transferable:
• Workers returning to domestic firms lose their accumulated
premium (selection, or work-life balance?)
• Labour mobility:
• Foreign firms are no more likely to hire workers from outside NZ
• But workers are somewhat more likely to leave the NZ labour
market within a year of leaving a foreign firm (selection, or
skills/networks?)

13. A complex policy conundrum
Returns to skill?
International
experience?
“Brain drain”?
Earnings inequality?
Aggregate earnings?
Human capital
accumulation?
Productivity?
Capital intensity?
International
networks?

14. Insights for Policy

15. Insights, not answers
Empirical research can help inform policy by
• Helping to prioritise efforts
• Helping to promote and justify interventions
• Describing the context
• Identifying and targeting particular groups
• Identifying unintended consequences to mitigate or manage
But…
• Only provides a partial picture
• Inherently backward looking
• No silver bullet – insights, not answers

16. Insights, not answers
Therefore…
• Programmes, not projects
• Need to focus on principles and mechanisms to inform
future policy development, not just on aggregate outcomes
observed in the past
• Communication and links to policy process are critical to
influence, not just inform, policy decisions