## Introduction and Main Findings

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### Context and scope
- Chapter prepared by Dirk Muir (lead author), Sergei Dodzin, Xinhao Han, Dongyeol Lee, and Ryota Nakatani, under the guidance of Thomas Helbling.
- Focus: productivity developments in Asia and the Pacific since the global financial crisis and implications for convergence, investment, and policy.

### Core questions addressed
- Has there been a productivity slowdown in Asia similar to that in advanced economies?
  - How large and extensive has it been?
  - Implications for convergence and outlook for productivity.
- How much of the slowdown is attributable to external versus domestic factors?
- Is there an investment malaise in Asia and linkages to advanced economies? Role of foreign direct investment (FDI) as a driver of business investment.

### Main conclusions
- Asia has experienced a productivity growth slowdown since the global financial crisis.
  - Slowdown most severe in the advanced economies of the region and in China.
  - In other emerging market economies and some developing economies of the region, the decline in productivity growth since the global financial crisis has been small.
- Drivers in Asia’s advanced economies and China similar to other advanced economies: less favorable demographics and smaller impetus from trade integration.
- Three reasons to prioritize reforms strengthening domestic productivity sources:
  - External factors seem less likely to contribute as much to productivity growth as in the past.
  - Demographics will increasingly weigh on productivity growth in a number of economies.
  - Structural change toward services, where productivity growth has been substantially lower than in manufacturing, presents a challenge.
- Positive features to build on:
  - R&D activity in the advanced economies of the region remains strong; challenge is strengthening the effectiveness of R&D spending in boosting productivity.
  - Many emerging market and developing economies can capitalize on increased FDI and improve educational achievements, infrastructure spending, and private domestic investment.
  - Reviving trade liberalization and integration would benefit productivity.

*Source: areo0517c3 - Introduction and Main Findings*

### The productivity picture: concepts, methods, and broad evidence
- Productivity concepts used:
  - Total factor productivity (TFP).
  - Labor productivity (output per worker or per hour worked).
- Assessment approaches:
  - Against past performance.
  - Relative to the technological frontier (United States used as the single point of comparison, United States = 100).
- Aggregate TFP regional overview:
  - Economic growth generally held up well in Asia since the global financial crisis compared to the precrisis period (2001–07) and other advanced economies.
  - Post-crisis growth relied more on factor accumulation than on TFP improvements.
- Group-specific findings:
  - Asia-Pacific advanced economies (Australia, Japan, Korea, Hong Kong SAR, New Zealand, and Singapore):
    - Growth about 1 percentage point lower on average after the global financial crisis.
    - Decline in TFP growth after the global financial crisis broadly comparable to that in other advanced economies.
  - China and India:
    - Decline in average growth has been smaller since the global financial crisis.
    - Average growth is close to 8 percent, although it has declined more recently in China.
    - TFP growth decline in India modest; China’s TFP growth decline is more substantial than its real GDP decline.
  - ASEAN-4 (Indonesia, Malaysia, the Philippines, and Thailand):
    - Real GDP and TFP growth after the global financial crisis remained relatively close to precrisis growth, with only a minor decline in both.
  - Other Asia-Pacific EMDEs:
    - Growth remained high and stable, with only a minor reduction after the global financial crisis; TFP data not available for all countries but some show similar patterns to real GDP growth.
- Convergence evidence:
  - Penn World Tables TFP indices relative to the United States (United States = 100) suggest relatively weak TFP convergence in China and India and in the ASEAN-4; Asia-Pacific advanced economies have lost some ground against the United States, similar to other advanced economies.
- Note on procyclicality:
  - TFP growth tends to be strongly procyclical over longer periods; 2008–14 trends expected to be broadly representative for 2015–16 given real GDP outcomes.

### Sectoral developments (labor productivity emphasis)
- Rationale: aggregate productivity reflects sectoral and firm-level developments; sectoral data provide insight on engines of productivity growth. Sectoral analysis relies on labor productivity measures.
- Key sectoral patterns (Japan, Korea, United States comparisons):
  - Labor productivity growth in services much lower than in manufacturing.
  - In Korea, services labor productivity improved since the global financial crisis; in Japan it remained weak.
  - In Korea, manufacturing labor productivity broadly similar to or stronger than in the United States; in both Korea and Japan, manufacturing labor productivity declined after the global financial crisis.
  - ICT sectors in Korea and Japan show relatively weak labor productivity growth compared to the United States.
  - Productivity convergence in services stalled in Korea and reversed in Japan relative to the United States.
- Shift-share decomposition (2004–07 vs. 2008–14):
  - Manufacturing accounted for about half of aggregate labor productivity growth (less in China).
  - Slowdown in manufacturing was an important reason for the overall productivity slowdown after the global financial crisis.
  - Labor productivity slowed in other sectors, including financial services.
  - Finance, real estate, and business services contributed between one-fifth and one-third of aggregate labor productivity growth but slowed after the global financial crisis and accounted for most structural change effects.

*Source: areo0517c3 - The Productivity Picture in Asia and the Pacific*

### Drivers of productivity: investment, trade, FDI, and absorptive capacity
- Fixed investment
  - Fixed investment contributes via capital intensity, embodied new technologies, and potential measurement bias.
  - Post-global-financial-crisis: rate of fixed investment (as percent of the stock of physical capital) slowed in Asia-Pacific advanced economies to rates broadly at par with other advanced economies.
  - Estimates by Adler and others (2017) suggest such declines in investment rates could explain a sizable reduction in TFP, on the order of ¼ to ½ of a percentage point.
  - In the ASEAN-4, investment rates broadly unchanged before and after the global financial crisis.
  - In China, India, and other EMDEs, investment rates increased and supported productivity.
  - Prospects/risks: fixed investment expected to remain relatively weak where rates slowed; China’s rebalancing toward consumption likely to slow investment rates and could weigh on productivity absent offsets.
- International trade
  - Trade openness has generally moved sideways or declined since the global financial crisis; trade unlikely to have supported productivity overall.
  - Exceptions: trade openness increased after the global financial crisis in Asia-Pacific advanced economies and in other EMDEs in the region, particularly intra-Asia-Pacific trade, reflecting outsourcing and supply-chain lengthening.
  - Overall, continued moderate trade growth implies little trade-related boost to productivity.
- Foreign Direct Investment (FDI)
  - FDI inflows (percent of GDP) increased in China, India, and the ASEAN-4 after the global financial crisis.
  - In Japan and Korea, FDI inflows broadly stable; both showed noticeable increases in FDI outflows.
  - Implication: FDI likely contributed to productivity increases mainly in emerging and developing Asia-Pacific economies after the global financial crisis.
  - Prospects/risks: FDI inflows into many EMDEs expected to remain strong; increased protectionism could slow or reverse supply-chain building and offshoring.
  - Empirical analysis suggests FDI supports domestic fixed investment within Asia as a whole, amplifying productivity effects; the role of FDI has become increasingly important over time, particularly since the global financial crisis.
- Absorptive capacity
  - Definition: factors enabling domestic economy to absorb positive influences (R&D, technology transfer); human capital is key.
  - Tertiary education enrollment (share of official tertiary education cohort population) — reported levels include:
    - European Union: 1992 = 32.5; 1997 = 44.8; 2001 = 52.3; 2008 = 62.6; 2014 = 67.7
    - United States: 1992 = 77.1; 1997 = 70.6; 2001 = 69.0; 2008 = 85.0; 2014 = 86.7
    - Japan: 1992 = 30.0; 1997 = 45.1; 2001 = 49.9; 2008 = 57.6; 2014 = 62.4
    - Korea: 1992 = 39.5; 1997 = 64.5; 2001 = 82.5; 2008 = 95.3; 2014 = 95.3
    - Indonesia: 1992 = 9.4; 1997 = 13.4; 2001 = 14.2; 2008 = 20.7; 2014 = 31.1
    - Malaysia: 1992 = 9.1; 1997 = 21.8; 2001 = 25.0; 2008 = 33.7; 2014 = 38.5
    - Philippines: 1992 = 25.8; 1997 = 27.5; 2001 = 30.3; 2008 = 29.4; 2014 = 35.8
    - Thailand: 1992 = 19.3; 1997 = 23.0; 2001 = 39.0; 2008 = 47.9; 2014 = 52.5
    - China: 1992 = 2.8; 1997 = 5.5; 2001 = 10.0; 2008 = 20.9; 2014 = 39.4
    - India: 1992 = 6.0; 1997 = 6.6; 2001 = 9.7; 2008 = 15.1; 2014 = 23.9
    - Bangladesh: 1992 = —; 1997 = 5.5; 2001 = 6.4; 2008 = 8.6; 2014 = 13.4
    - Nepal: 1992 = 5.4; 1997 = 4.8; 2001 = 4.5; 2008 = 11.3; 2014 = 15.8
  - Trends: tertiary enrollment shares broadly increased across Asian economies; in advanced economies the rate of increase slowed since the global financial crisis, contributing to productivity slowdown; China’s tertiary share doubled between 2008 and 2014.
  - Public infrastructure: public capital stocks high in most Asia-Pacific advanced economies and China; public-capital per capita ratio accelerated in China and the ASEAN-4 after the global financial crisis.

### Biased technical change and inclusiveness (Box 3.1)
- Automation has increased substitution away from labor; multi-factor cost approach measures bias across five input factors and four industries.
- Findings (1995–2009 over subperiods):
  - General tendency toward a positive bias in capital goods and a negative bias against low-skilled labor in China, Japan, Korea, and the United States.
  - Capital bias stronger in China but declining over time.
  - Mild bias toward high-skilled labor in research-intensive industries and high-knowledge services.
  - Strong negative bias against low-skilled labor in the United States; least negative bias in China.
- Implications:
  - Industries with positive capital bias should show higher labor productivity, but aggregate impact depends on labor reallocation capacity.
  - Policymakers should combine productivity-enhancing measures with inclusive growth strategies and focus on human capital and enabling environment to mitigate adverse distributional effects.

*Source: Box 3.1. Biased Technical Change and Productivity (prepared by Dirk Muir)*

### Empirical evidence: sectoral and country-level analyses
- Sectoral panel regression (1995–2007, 24 sectors across 19 advanced economies including Japan, Korea, and Taiwan Province of China)
  - Specification relates sectoral labor productivity growth to productivity gap (convergence) interacted with explanatory variables and controls for changes in capital-labor ratio.
  - Five explanatory variables (all scaled by value added or gross output in the sector): R&D expenditure; Exports; Imports; Inward FDI; Outward FDI.
- Key sectoral findings
  - Labor productivity grows faster in industries with larger labor productivity gaps (catch-up growth); relationship statistically significant.
  - Higher R&D spending raises labor productivity; impact greater in sectors closer to U.S. levels.
  - No substantial differences between manufacturing and services in R&D productivity impact in the sample, though R&D spending small in services relative to manufacturing.
  - Higher trade openness positively and significantly impacts labor productivity growth; increase in import openness by 1 percentage point yields a larger positive impact than an equivalent increase in export openness.
  - Imports of intermediate inputs are an important channel through which imports raise labor productivity.
  - Inward FDI has a statistically significant positive impact on labor productivity growth.
  - Outward FDI has a negative impact on domestic labor productivity growth (possible crowding-out mechanism).
- Thought experiment (counterfactual)
  - Increasing R&D, imports, exports, and inward FDI from the 25th percentile to the 75th percentile of the sample (from “low” to “high” performer) implies substantial productivity increases from policies promoting trade integration, import competition, and inward FDI.
  - Caveats: causality not definitively established; reverse causality and omitted variable bias possible; country-industry fixed effects capture many domestic factors.

- Country-level panel evidence (1980–2014) across Asia-Pacific economies
  - Domestic factors (such as R&D) generally have less impact than external factors (such as FDI) on aggregate TFP growth.
  - Some evidence that sources of TFP growth shifted in favor of domestic factors (including financial development and absorptive capacity) since the global financial crisis—important if advanced-economy demand and cross-country investment flows slow.

### R&D trends and implications
- R&D spending has increased notably among Asian countries since the global financial crisis, converging toward United States and other advanced-economy levels.
  - Korea has become a leader in R&D spending.
  - As of 2014, China was at par with the average R&D spending in the European Union and with spending in Singapore.
- Patent-application data corroborate R&D spending trends; strong increases in patents in China and Korea stand out.
- Despite increased R&D spending, productivity growth did not rise as much as expected, implying:
  - Other offsetting factors, or
  - Effectiveness issues: increased spending has not fully translated into marketable innovation and productivity gains.
- Much R&D spending in Asia undertaken by large companies, especially multinationals; diffusion from leading firms may have slowed.
- Closing of the R&D gap largely reflects manufacturing developments rather than services; R&D in services remains lagging.

*Source: areo0517c3 - Research & development trends and implications*

### Implications and policy priorities by country group
- Overall assessment
  - Asia experienced a productivity growth slowdown after the global financial crisis; little, if any, convergence to the technological frontier is observed.
  - Productivity growth likely to remain low for some time, with demographics increasingly contributing to the slowdown.
  - Magnitude and nature differ across economies.
- Most severe slowdown: advanced Asia-Pacific economies and China.
  - Common drivers in advanced economies: slowing investment; little impetus from trade; slowing human capital formation; reallocation to less productive sectors; aging population.
  - Services-sector performance has lagged in some services relative to the United States; R&D activity in advanced economies of the region remains strong or has increased.
  - China: increased R&D spending and rapid educational attainment progress; trade openness declined after initial gains; resource misallocation and incentive distortions (e.g., sectoral overcapacity) hold back productivity.
- Emerging markets and some low-income economies (including India and the ASEAN-4)
  - Decline in productivity growth since the global financial crisis has been small, but little progress in convergence to the technology frontier.
- Policy priorities
  - Continue pursuing further trade liberalization given strong productivity benefits.
  - Tailor domestic policies by country:
    - Advanced economies: strengthen effectiveness of R&D spending; raise productivity in services through increased competition.
    - India: improve productivity in agriculture (about half of Indian workers employed in agriculture); address structural bottlenecks and enhance market efficiency (liberalize commodity markets; give farmers more flexibility in distribution and marketing); administer input subsidies via direct cash transfers rather than underpricing of agricultural inputs.
    - Other EMDEs: capitalize on rises in FDI inflows by increasing related productivity spillovers through further increases in absorptive capacity and domestic investment.
    - Japan and Korea: continue leadership in human capital formation; ASEAN-4 should strengthen quality and flexibility of domestic education systems.
    - Where public infrastructure gaps remain, expand public infrastructure.

*Source: areo0517c3 - Conclusions and Policy Implications*

### Empirical annex highlights (selected quantitative results)
- Annex Table 3.2.2. Baseline country-level TFP results (selected coefficients and statistics)
  - Asia-Pacific: R&D Stock 0.005*** (0.001); FDI Stock 0.089*** (0.007); Imports 20.001*** (0.000); Financial Development 0.002*** (0.000); Countries 145; Observations 454; R-squared 0.93
  - Asian AEs: R&D Stock 0.019*** (0.006); FDI Stock 0.067*** (0.024); Imports 0.001** (0.000); Financial Development 0.001 (0.001); Countries 93; Observations 153; R-squared 0.81
  - Other A-PAEs: R&D Stock 0.005*** (0.001); FDI Stock 0.103*** (0.009); Imports 20.003*** (0.001); Financial Development 0.002*** (0.001); Countries 36; Observations 330; R-squared 0.90
  - EMEs: R&D Stock 0.008*** (0.003); FDI Stock 0.014*** (0.005); Imports 0.001*** (0.000); Financial Development 0.000** (0.000); Countries 67; Observations 1,105; R-squared 0.87
  - EMDEs: R&D Stock 0.001 (0.001); FDI Stock 0.046*** (0.006); Imports 20.002*** (0.000); Financial Development 0.001 (0.001); Countries 70; Observations 2,2074; R-squared 0.93
- Annex Table 3.2.3. Absorptive-capacity specifications (selected)
  - Asia-Pacific (column 1): R&D Stock 0.012*** (0.004); FDI Stock 0.118*** (0.012); Imports 20.001* (0.001); Financial Development 0.001* (0.001); Interaction of FDI Stock and Human Capital 0.002** (0.001); Countries 12; Observations 203; R-squared 0.95
  - Asia-Pacific (column 2): R&D Stock 0.005*** (0.001); FDI Stock 0.087*** (0.008); Imports 20.001*** (0.000); Financial Development 0.002*** (0.000); Interaction of FDI Stock and Human Capital 0.002** (0.001); Interaction of FDI Stock and Public Capital 20.011 (0.014); Countries 13; Observations 430; R-squared 0.93
- Annex Table 3.2.4. Asia before and after the Global Financial Crisis (selected)
  - 1980–2007: R&D Stock 0.010*** (0.003); FDI Stock 0.127*** (0.014); Imports 20.001 (0.001); Financial Development 0.002** (0.001); Countries 12; Observations 137; R-squared 0.97
  - 2008–14: R&D Stock 0.090*** (0.027); FDI Stock 0.107*** (0.027); Imports 20.003*** (0.001); Financial Development 0.001 (0.001); Interaction of FDI Stock and Human Capital 0.002** (0.001); Countries 11; Observations 66; R-squared 0.98
- Annex Table 3.2.5. Complementarity between Domestic Investment and FDI in Emerging and Developing Asia and the Pacific (selected)
  - 1978–2015: Lagged Investment 0.690*** (0.036); Inward FDI Flows 0.133** (0.060); Lagged Real Growth 0.156** (0.072); Interest Rate 0.038** (0.016); Observations 470; R-squared 0.84
  - 2008–15: Lagged Investment 0.325*** (0.078); Inward FDI Flows 0.566*** (0.122); Lagged Real Growth 0.144 (0.195); Interest Rate 20.507 (0.361); Observations 147; R-squared 0.83

*Source: Annex Tables and IMF staff calculations in areo0517c3*

### India-specific findings and implications
- Data limitation: No data available for India after 2007 for sectoral series used in some analyses.
- Historical role of reallocation:
  - In China and India, labor reallocation from agriculture to other sectors generated labor productivity gains.
- Conceptual drivers emphasized: technological progress and organizational change; both depend on incentives and absorptive capacity (human capital, financial depth, institutions).
- Empirical approach (sectoral): sample covered 24 sectors across 19 advanced economies for 1995–2007; regressions include R&D expenditure, exports, imports, inward FDI, outward FDI.
- Key empirical findings relevant for India:
  - Catch-up growth: faster labor productivity where productivity gaps are larger.
  - Higher R&D spending raises labor productivity; effectiveness greater in sectors closer to U.S. levels.
  - Import openness (especially imports of intermediate inputs) has a strong positive impact on labor productivity; a 1 percentage point increase in import openness yields a larger positive impact than an equivalent increase in export openness.
  - Inward FDI positively impacts labor productivity; outward FDI negatively impacts domestic labor productivity growth.
- Implications for India
  - Continued gains in aggregate labor productivity would be aided by:
    - Further R&D investment and improved effectiveness of R&D in translating into marketable innovations.
    - Greater trade integration and import openness, especially imports of intermediate inputs.
    - Policies to attract inward FDI and strengthen absorptive capacity (human capital, infrastructure, financial development, institutions).
  - Risks: stagnant global trade and cross-country investment flows and limited diffusion of R&D-generated innovations beyond leading firms.

*Source: areo0517c3 - Section 5. India and chapter evidence*

*Source: areo0517c3 (IMF staff calculations and analysis, AREO chapter 3, April 2017).*

### Introduction and Main Findings

### Introduction and Main Findings

### Context and chapter authorship
- Chapter prepared by Dirk Muir (lead author), Sergei Dodzin, Xinhao Han, Dongyeol Lee, and Ryota Nakatani, under the guidance of Thomas Helbling.
- Nearly 10 years after the global financial crisis, the prospect of mediocre future growth remains a concern driven by:
  - A recent slowdown in productivity growth in many advanced economies.
  - Weakness in business investment, which channels new technology and innovation into productivity.

### Core questions addressed
- Has there been a productivity slowdown in Asia similar to that in advanced economies? If so:
  - How large and extensive has it been?
  - What have been the implications for convergence?
  - What is the outlook for productivity?
- How much of the slowdown can plausibly be attributed to external factors versus domestic factors?
- Is there an investment malaise in Asia and can it be related to that in advanced economies elsewhere? How important is foreign direct investment (FDI) as a driver of business investment?

### Main conclusions and policy priorities
- Asia has experienced a productivity growth slowdown since the global financial crisis.
  - The slowdown has been most severe in the advanced economies of the region and in China.
  - In other emerging market economies and some developing economies of the region, the decline in productivity growth since the global financial crisis has been small.
- Drivers of the slowdown in Asia’s advanced economies and China appear similar to other advanced economies: less favorable demographics and a smaller impetus from trade integration.
- Three reasons reforms to strengthen domestic sources of productivity growth should be prioritized in Asia:
  - External factors seem less likely to contribute as much to productivity growth as in the past.
  - Demographics will increasingly weigh on productivity growth in a number of economies.
  - Structural change toward services, where productivity growth has been substantially lower than in manufacturing, presents a challenge.
- Positive features to build on:
  - R&D activity in the advanced economies of the region remains strong; a policy challenge is strengthening the effectiveness of R&D spending in boosting productivity.
  - Many emerging market and developing economies can capitalize on achievements and favorable external factors such as increased FDI, and improve educational achievements, infrastructure spending, and private domestic investment.
  - Reviving trade liberalization and integration would benefit productivity.

---

### The Productivity Picture in Asia and the Pacific

- Productivity concepts used:
  - Total factor productivity (TFP).
  - Labor productivity (output per worker or per hour worked).
- Relationship noted:
  - TFP increases mean given capital and labor produce more output over time.
  - Labor productivity increases with TFP and with capital deepening; TFP and labor productivity growth are expected to be positively, but not necessarily strongly, correlated.
- Two assessment approaches:
  - Against past performance.
  - Relative to the technological frontier (United States used as the single point of comparison, United States = 100).

---

### Aggregate Total Factor Productivity (TFP) — regional overview
- Charts compare average rates of growth over four periods to abstract from cyclical fluctuations.
- Broad picture:
  - Economic growth generally held up well in Asia since the global financial crisis compared to the precrisis period (2001–07) and other advanced economies.
  - The difference between real GDP and TFP growth suggests post-crisis growth has been relatively more extensive (driven more by factor accumulation than by TFP improvements).
- Group-specific findings:
  - Asia-Pacific advanced economies (Australia, Japan, Korea, Hong Kong SAR, New Zealand, and Singapore):
    - Growth was about 1 percentage point lower on average after the global financial crisis.
    - This decline is roughly comparable to the outcome in the United States but better relative to other advanced economies as a group.
    - The decline in TFP growth after the global financial crisis is broadly comparable to that in other advanced economies.
  - China and India:
    - The decline in average growth has been smaller since the global financial crisis.
    - Average growth is close to 8 percent, although it has declined more recently in China.
    - TFP growth decline in India is reflected modestly; China’s TFP growth decline is more substantial than its real GDP decline.
  - ASEAN-4 (Indonesia, Malaysia, the Philippines, and Thailand):
    - Real GDP and TFP growth after the global financial crisis remained relatively close to precrisis growth, with only a minor decline in both.
  - Other Asia-Pacific emerging market and developing economies:
    - Growth remained high and stable, with only a minor reduction after the global financial crisis.
    - TFP data are not available for all countries in this group, but some show TFP patterns similar to real GDP growth.

- Data timing and procyclicality:
  - TFP growth tends to be strongly procyclical over longer periods.
  - Since real GDP growth broadly held up in 2015–16 compared to 2008–14, TFP trends in 2008–14 are expected to remain broadly representative for the more recent period.

- Convergence evidence:
  - Using Penn World Tables TFP indices relative to the United States (United States = 100) suggests:
    - Relatively weak TFP convergence in China and India and in the ASEAN-4.
    - Asia-Pacific advanced economies have lost some ground against the United States, similar to other advanced economies.

---

### Productivity Developments by Sector (labor productivity focus)
- Rationale:
  - Aggregate productivity reflects sectoral and firm-level developments; sectoral data provide insight on engines of productivity growth.
  - Sectoral analysis relies on labor productivity measures due to data availability; labor productivity is complementary to TFP.
- Key sectoral patterns (Japan, Korea, United States comparisons):
  - Labor productivity growth in services has been much lower than in manufacturing.
  - In Korea, services labor productivity improved since the global financial crisis; in Japan, it has remained weak.
  - In Korea, manufacturing labor productivity has been broadly similar to or stronger than in the United States; in both Korea and Japan, manufacturing labor productivity declined after the global financial crisis.
  - ICT sectors in Korea and Japan show relatively weak labor productivity growth compared to the United States—concerning because ICT is likely to remain important for economy-wide labor productivity gains.
  - Productivity convergence in services stalled in Korea and reversed in Japan relative to the United States.

- Sectoral contribution decomposition (shift-share analysis, 2004–07 vs. 2008–14):
  - Method: real labor productivity growth decomposed into “within” effects (productivity changes generated within sectors) and “structural change” effects (changes from shifting sectoral shares).
  - Highlights:
    - Sectoral labor productivity growth rates confirm productivity growth in Asia slowed after the global financial crisis.
    - Manufacturing sectors accounted for about half of aggregate labor productivity growth (less in China, where contributions are spread across sectors).
    - The slowdown in manufacturing was an important reason for the overall productivity slowdown following the global financial crisis.
    - Labor productivity also slowed in other sectors, including financial services.
    - Finance, real estate, and business services contributed substantially to aggregate labor productivity growth, accounting for between one-fifth and one-third of that growth, but their labor productivity growth slowed after the global financial crisis and these sectors accounted for most structural change effects.

*Source: areo0517c3 - Introduction and Main Findings*

### 5. India

### 5. India

### Sectoral data note
- No data available for India after 2007.

### Reallocation and aggregate labor productivity
- In China and India, labor productivity gains were in part generated by continuing reallocation from agriculture to other sectors—a phenomenon common for many developing economies.
- The growing share of higher-productivity sectors in the economy has generally lifted aggregate labor productivity growth, all else being equal.

### Conceptual drivers of productivity growth
- Fundamental drivers: technological progress (new technologies) and new ways of organizing production processes.
- Both drivers depend on economic incentives and preconditions that create an enabling environment.
- Economic integration and openness can boost productivity via:
  - technology and knowledge diffusion,
  - information-sharing,
  - increased competition from foreign firms,
  - larger markets enabling greater specialization and more productive supply chain arrangements.
- Absorptive capacity is critical: the ability of one factor (for example, high-quality R&D or high-quality infrastructure) to enrich another factor (for example, FDI) in stimulating productivity growth.
- Other absorptive-capacity contributors: human capital, financial depth, and institutions.

### Empirical approach (sectoral)
- Data sample: sectoral labor productivity growth in 24 sectors across 19 advanced economies (including Japan, Korea, and Taiwan Province of China) for the sample period 1995–2007.
- Specification: panel regression relating sectoral labor productivity growth to the productivity gap (convergence) interacted with explanatory variables and controlling for changes in the capital-labor ratio.
- Five explanatory variables (all scaled by value added or gross output in the sector):
  1. R&D expenditure
  2. Exports
  3. Imports
  4. Inward FDI
  5. Outward FDI

### Key empirical findings (sectoral)
- Labor productivity grows faster in industries with larger labor productivity gaps (catch-up growth); the relationship is statistically significant.
- Higher R&D spending raises labor productivity.
  - The impact of R&D spending is greater in sectors where labor productivity levels are already close to U.S. levels.
  - No substantial differences found between manufacturing and services in the magnitude of the productivity impact of R&D in the sample, though R&D spending has been small in services relative to manufacturing.
- Higher trade openness has a positive and significant impact on labor productivity growth.
  - An increase in import openness by 1 percentage point yields a larger positive impact than an equivalent increase in export openness.
  - Imports of intermediate inputs are an important channel through which imports raise labor productivity.
- Inward FDI has a statistically significant positive impact on labor productivity growth.
- Outward FDI has a negative impact on domestic labor productivity growth (possible mechanism: firms invest abroad in more productive markets, crowding out domestic investment).

### Thought experiment on policy levers (sectoral)
- A counterfactual: increasing main productivity drivers (R&D, imports, exports, inward FDI) from the 25th percentile to the 75th percentile of the sample (shifting from a “low” to a “high performer”) implies:
  - Policies aimed at increased trade integration, greater import competition, and greater inward FDI would generate substantial productivity increases.
- Caveats:
  - The relationship between external factors and labor productivity growth is complex and causality is not definitively established.
  - Reverse causality and omitted variable bias are possible.
  - Country-industry fixed effects capture many domestic factors that cannot be separately recovered for economic interpretation.

### Broader country-level evidence (1980–2014)
- Country-level panel regressions across Asia-Pacific economies (including Asian advanced economies, China, India, the ASEAN-4, and some Asia-Pacific EMDEs) indicate:
  - Domestic factors (such as R&D) generally have less impact than external factors (such as FDI) on aggregate TFP growth.
  - There is some evidence that sources of TFP growth have shifted in favor of domestic factors (including financial development and absorptive capacity) since the global financial crisis—important if advanced-economy demand and cross-country investment flows slow.

### Research & development trends and implications
- Overall R&D spending has increased notably among Asian countries since the global financial crisis, converging toward United States and other advanced-economy levels.
  - Korea has become a leader in R&D spending.
  - As of 2014, China was at par with the average R&D spending in the European Union and with spending in Singapore.
- Patent-application data (absolute and per unit of GDP) corroborate R&D spending trends; strong increases in patents in China and Korea stand out.
- Despite increased R&D spending since the global financial crisis, productivity growth did not increase as much as expected, suggesting either:
  - Other factors offset the beneficial impact of R&D, or
  - Effectiveness issues: increased spending has not yet fully translated into marketable innovation and productivity gains.
- Much R&D spending in Asia is undertaken by large companies, especially multinationals; diffusion from leading firms may have slowed.
- The closing of the R&D gap largely reflects developments in manufacturing rather than services; R&D in services remains lagging, which could help explain relatively lower productivity growth in services.

### Implications for India (drawing on chapter evidence)
- Reallocation of labor out of agriculture has supported labor productivity gains historically.
- Continued gains in aggregate labor productivity would be aided by:
  - Further R&D investment and improved effectiveness of R&D in translating into marketable innovations,
  - Greater trade integration and import openness, especially imports of intermediate inputs,
  - Policies that attract inward FDI and strengthen absorptive capacity (human capital, infrastructure, financial development, institutions).
- Risks to productivity growth include stagnant global trade and cross-country investment flows and limited diffusion of R&D-generated innovations beyond leading firms.

*Source: IMF staff calculations and analysis in AREO chapter 3 (Regional Economic Outlook: Asia and Pacific, April 2017).*

### 3. ThE “NEw MEdIOCRE” ANd ThE OUTLOOK fOR PROdUCTIvITy IN AsIA

### 3. ThE “NEw MEdIOCRE” ANd ThE OUTLOOK fOR PROdUCTIvITy IN AsIA

### Fixed Investment
- Fixed investment contributes to productivity through:
  - increased capital intensity (lifts labor productivity for a given amount of labor).
  - new technologies embodied in new capital.
  - potential measurement bias toward capital, implying a downshift in investment could lower TFP (see Box 3.1).
- Post-global-financial-crisis developments:
  - Rate of fixed investment (as percent of the stock of physical capital) slowed in Asia-Pacific advanced economies to rates broadly at par with other advanced economies.
  - Estimates by Adler and others (2017) suggest such declines in investment rates could explain a sizable reduction in TFP, on the order of ¼ to ½ of a percentage point.
  - In the ASEAN-4, investment rates were broadly unchanged before and after the global financial crisis.
  - In several regional countries (including China, India, and other EMDEs in the region), investment rates increased and supported productivity.
- Prospects and risks:
  - Fixed investment is expected to remain relatively weak for some time in economies where investment rates slowed after the global financial crisis.
  - In China, economic rebalancing toward consumption implies investment rates are likely to slow, which, absent offsetting measures, could weigh on productivity.

### International Trade
- Trade as a channel for technology transfer; overall post-crisis patterns:
  - Trade openness (exports and imports) has generally moved sideways or declined since the global financial crisis.
  - As a result, trade is unlikely to have supported productivity overall.
  - Prospects: continued moderate trade growth, with little change in export or import ratios; a trade-related boost to productivity overall thus seems unlikely (Constantinescu, Mattoo, and Ruta 2016).
- Exceptions and regional patterns:
  - Trade openness increased after the global financial crisis in Asia-Pacific advanced economies and in other EMDEs in the region.
  - Increase is particularly prominent in intra-Asia-Pacific trade, partly reflecting further outsourcing of manufacturing from advanced economies to EMDEs in the region and continued building/lengthening of supply chains.
  - Evidence of supply-chain lengthening is consistent with developments seen in Europe (e.g., Germany and central European countries).

### Foreign Direct Investment (FDI)
- FDI roles:
  - FDI can be an engine of productivity growth; effects depend on inward versus outward FDI.
- Post-global-financial-crisis developments:
  - As percent of GDP, FDI inflows increased in China, India, and the ASEAN-4 after the global financial crisis.
  - In Japan and Korea, FDI inflows remained broadly stable; both registered a noticeable increase in FDI outflows.
  - Implication: FDI likely contributed to productivity increases mainly in emerging and developing Asia-Pacific economies after the global financial crisis.
- Prospects and risks:
  - FDI inflows into many EMDEs in the region are expected to remain strong, supporting further productivity increases.
  - Risks from increased protectionism could slow or reverse building of supply chains and offshoring.
- Additional channel:
  - Empirical analysis suggests FDI supports domestic fixed investment within Asia as a whole, amplifying productivity effects; the role of FDI has become increasingly important over time, particularly since the global financial crisis.

### Absorptive Capacity
- Definition and importance:
  - Absorptive capacity: factors enabling domestic economy to absorb positive influences (R&D, technology transfer). Human capital is a key element.
- Tertiary education enrollment (share of official tertiary education cohort population) — reported levels:
  - European Union: 1992 = 32.5; 1997 = 44.8; 2001 = 52.3; 2008 = 62.6; 2014 = 67.7
  - United States: 1992 = 77.1; 1997 = 70.6; 2001 = 69.0; 2008 = 85.0; 2014 = 86.7
  - Japan: 1992 = 30.0; 1997 = 45.1; 2001 = 49.9; 2008 = 57.6; 2014 = 62.4
  - Korea: 1992 = 39.5; 1997 = 64.5; 2001 = 82.5; 2008 = 95.3; 2014 = 95.3
  - Indonesia: 1992 = 9.4; 1997 = 13.4; 2001 = 14.2; 2008 = 20.7; 2014 = 31.1
  - Malaysia: 1992 = 9.1; 1997 = 21.8; 2001 = 25.0; 2008 = 33.7; 2014 = 38.5
  - Philippines: 1992 = 25.8; 1997 = 27.5; 2001 = 30.3; 2008 = 29.4; 2014 = 35.8
  - Thailand: 1992 = 19.3; 1997 = 23.0; 2001 = 39.0; 2008 = 47.9; 2014 = 52.5
  - China: 1992 = 2.8; 1997 = 5.5; 2001 = 10.0; 2008 = 20.9; 2014 = 39.4
  - India: 1992 = 6.0; 1997 = 6.6; 2001 = 9.7; 2008 = 15.1; 2014 = 23.9
  - Bangladesh: 1992 = —; 1997 = 5.5; 2001 = 6.4; 2008 = 8.6; 2014 = 13.4
  - Nepal: 1992 = 5.4; 1997 = 4.8; 2001 = 4.5; 2008 = 11.3; 2014 = 15.8
  - Note: table footnotes specify year availability differences for some countries.
- Trends and implications:
  - Tertiary enrollment shares broadly increased across Asian economies over past decades.
  - In advanced economies, where initial levels were already high, the rate of increase has slowed since the global financial crisis; this slowdown in building human capital is a contributing factor to the productivity slowdown in advanced economies (Adler and others 2017).
  - In other countries, tertiary shares increased rapidly after the global financial crisis; China’s share doubled between 2008 and 2014.
- Public infrastructure:
  - Public capital stocks are high in most Asia-Pacific advanced economies and China compared to other advanced economies and the United States.
  - In China and the ASEAN-4, the public-capital per capita ratio accelerated after the global financial crisis, reflecting increasing investment shares.
  - Where public infrastructure gaps remain, expanding public infrastructure is a priority for some economies.

### Conclusions and Policy Implications
- Overall assessment:
  - Asia experienced a productivity growth slowdown after the global financial crisis; little, if any, convergence to the technological frontier is observed.
  - Productivity growth is likely to remain low for some time, with demographics increasingly contributing to the slowdown.
  - Magnitude and nature of the slowdown differ across economies in the region.
- By subregion and country:
  - Most severe slowdown (magnitude): advanced Asia-Pacific economies and China.
  - Common drivers in advanced economies: slowing investment, little impetus from trade (broadly unchanged trade openness), slowing human capital formation, reallocation to less productive sectors, and aging population.
  - Services-sector performance has lagged in some services relative to the United States; R&D activity in advanced economies of the region remains strong or has increased.
  - China: increased R&D spending and rapid educational attainment progress, but trade openness has declined after initial gains and resource misallocation and incentive distortions (e.g., sectoral overcapacity) hold back productivity.
  - Emerging markets and some low-income economies (including India and the ASEAN-4): decline in productivity growth since the global financial crisis has been small, but little progress in convergence to the technology frontier.
- Policy priorities:
  - Continue pursuing further trade liberalization given strong productivity benefits, even though further trade liberalization may be more difficult to achieve.
  - Tailor domestic policies by country:
    - Advanced economies: strengthen effectiveness of R&D spending; raise productivity in services sectors through increased competition to spur innovation and adaptation (see country cases such as Australia and Singapore in Box 3.2).
    - India: improve productivity in agriculture (about half of Indian workers employed in agriculture); address structural bottlenecks and enhance market efficiency (liberalize commodity markets; give farmers more flexibility in distribution and marketing); administer input subsidies via direct cash transfers rather than underpricing of agricultural inputs, since input underpricing has had large negative impacts on agricultural output.
    - Other EMDEs: capitalize on rises in FDI inflows by increasing related productivity spillovers through further increases in absorptive capacity and domestic investment.
    - Japan and Korea: continue leadership in human capital formation; ASEAN-4 should strengthen quality and flexibility of domestic education systems.
    - Where noticeable public infrastructure gaps remain, expand public infrastructure.

### Box — The Issue of Biased Technical Change (Box 3.1)
- Context:
  - Automation in manufacturing and services has increased substitution away from labor to automated processes; technical bias affects productivity, factor compensation, and employment.
  - Important policy question: how to reconcile labor savings from automation with productive employment elsewhere in the economy.
- Empirical framework:
  - Multi-factor cost approach (Binswanger 1974): change in factor shares across five input factors (capital goods, high-skilled labor, medium-skilled labor, low-skilled labor, intermediate goods) across four industries (agriculture; food, textiles, and leather; machinery and equipment; finance).
  - Bias toward factor i, B_i(t), defined as change in share S_i(t) for a given set of relative prices; positive B_i(t) indicates shift toward increased use of the factor.
  - For capital stock K, bias B_K(t) measured as:
    - B_K(t) ≈ (s_Kt+1 − s_Kt)/s_Kt, given cost of capital p_K, wage w, and price of intermediate goods p_I.
- Findings (1995–2009 over periods: 1995–96; 1997–2000; 2001–07; 2008–09):
  - General tendency toward a positive bias in capital goods and a negative bias against low-skilled labor in all countries considered (China, Japan, Korea, and the United States for comparison).
  - Capital bias is stronger in China, consistent with relative capital scarcity, though the bias is declining over time.
  - Mild bias toward high-skilled labor in research-intensive industries (machinery and equipment) and high-knowledge services (finance).
  - Strong negative bias against low-skilled labor in the most technically advanced country (the United States); least negative bias in China.
  - In China, bias toward high-skilled labor is observed across more industries, consistent with relative scarcity.
- Implications:
  - Industries with positive bias toward capital goods should demonstrate higher labor productivity.
  - Aggregate productivity impact depends on where labor is reallocated and economy’s ability to redeploy workers without increasing unemployment.
  - Policymakers should combine industry-level productivity increases with inclusive growth strategies.
  - Widespread negative bias toward low-skilled labor and positive bias toward high-skilled labor imply that increasing human capital and improving the economic environment could mitigate adverse effects from the ongoing transition implied by strong technical bias.

*International Monetary Fund | April 2017*

### Box 3.1. Biased Technical Change and Productivity

### Box 3.1. Biased Technical Change and Productivity

### Technical biases in major sectors
- Figure 3.1.1 (Technical Biases in Major Sectors) is based on World Input Output Database and IMF staff calculations and displays sectoral technical biases across periods 1995–96, 1997–2000, 2001–07, and 2008–09 for major economies (data labels use ISO country codes).
- Sectors covered in the analysis include Agriculture; Food, Textiles, and Leather; Machinery and Equipment; and Finance.
- Sectoral measures examine bias across inputs: Capital; High-skilled labor; Medium-skilled labor; Low-skilled labor; Intermediate goods.

### Policy recommendations: government role to augment productivity
- The focus is on governments improving their role through engagement with the private sector rather than prescribing industrial policy.
- A three-pronged approach for government facilitation:
  - Providing infrastructure through public investment, or by facilitating private efforts.
  - Putting in place a strong regulatory environment and secure legal framework in which to conduct business, have ownership, and engage smoothly with capital and labor.
  - Establishing public institutions that can serve as public goods for the private sector and provide quality information.
- Governments should avoid being solely dependent on the public sector to “mandate” productivity growth; instead, limited government funds can be used more efficiently to facilitate private involvement.

### Case example and institutional instruments (Australia)
- Australia illustrates public institutions acting as public goods that signal needs to the private sector, provide comprehensive information, and validate private initiatives.
- Institutional examples and roles:
  - Infrastructure Australia: identifies infrastructure needs and evaluates plans from governments and the private sector.
  - Productivity Commission: provides analysis on the state of productivity growth and advice on legislation as an arm’s-length observer.
- Legislative and spending complements:
  - Special studies (for example, the Competition Policy Review) are used to strengthen the legal and regulatory environment to simplify conducting business.
  - Public sector engages innovatively in trade policy (for example, intellectual property protections under the now-defunct Trans-Pacific Partnership agreement).
- Programs to incubate and stimulate productivity-enhancing industries:
  - National Innovation and Science Agenda (NISA) aims to incubate industries perceived as future leaders in productivity (for example, information and communication technology).
  - NISA’s approach includes: increasing public spending on many smaller initiatives over five years; addressing perceived gaps in critical science capabilities and access to quality private funding; and simplifying business regulation and interaction with the public sector.
- Note on evaluation:
  - Some segments of Australia’s approach are still new, and their effectiveness has yet to be evaluated (especially the new public initiatives and the NISA). The three-pronged approach is presented as a viable way forward to increase productivity in an economy with slowing productivity.

### Comparative note
- Some economies in the region (for example, Singapore) adapt similar approaches but with varying degrees of direct government engagement; Australia’s model emphasizes institutional frameworks and information with limited direct funding, whereas other approaches may feature more active government involvement.

*This box was prepared by Dirk Muir.*

### Annex Table 3.2.2. Baseline Country-Level Total Factor Productivity Results

### Annex Table 3.2.2. Baseline Country-Level Total Factor Productivity Results

### Regression coefficients and statistics by country group
- Asia-Pacific
  - R&D Stock 0.005*** (0.001)
  - FDI Stock 0.089*** (0.007)
  - Imports 20.001*** (0.000)
  - Financial Development 0.002*** (0.000)
  - Countries 145
  - Observations 454
  - R-squared 0.93
- Asian AEs
  - R&D Stock 0.019*** (0.006)
  - FDI Stock 0.067*** (0.024)
  - Imports 0.001** (0.000)
  - Financial Development 0.001 (0.001)
  - Countries 93
  - Observations 153
  - R-squared 0.81
- Other A-PAEs
  - R&D Stock 0.005*** (0.001)
  - FDI Stock 0.103*** (0.009)
  - Imports 20.003*** (0.001)
  - Financial Development 0.002*** (0.001)
  - Countries 36
  - Observations 330
  - R-squared 0.90
- EMEs
  - R&D Stock 0.008*** (0.003)
  - FDI Stock 0.014*** (0.005)
  - Imports 0.001*** (0.000)
  - Financial Development 0.000** (0.000)
  - Countries 67
  - Observations 1,105
  - R-squared 0.87
- EMDEs
  - R&D Stock 0.001 (0.001)
  - FDI Stock 0.046*** (0.006)
  - Imports 20.002*** (0.000)
  - Financial Development 0.001 (0.001)
  - Countries 70
  - Observations 2,2074
  - R-squared 0.93

### Notes on estimation
- white’s heteroscedasticity robust standard errors are in parentheses.
- Constants, country fixed effects, and year fixed effects are included but not reported.
- AEs 5 advanced economies; A-P 5 Asia-Pacific; EMdEs 5 emerging market and developing economies; fdI 5 foreign direct investment; R&d 5 research and development.
- Significance: *p < .10; **p < .05; ***p < .01.
- source: IMf staff calculations.

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### Annex Table 3.2.3. Absorptive Capacity in Asia

### Regression coefficients and statistics for absorptive-capacity specifications
- Asia-Pacific (column 1)
  - R&D Stock 0.012*** (0.004)
  - FDI Stock 0.118*** (0.012)
  - Imports 20.001* (0.001)
  - Financial Development 0.001* (0.001)
  - Interaction of FDI Stock and Human Capital 0.002** (0.001)
  - Countries 12
  - Observations 203
  - R-squared 0.95
- Asia-Pacific (column 2)
  - R&D Stock 0.005*** (0.001)
  - FDI Stock 0.087*** (0.008)
  - Imports 20.001*** (0.000)
  - Financial Development 0.002*** (0.000)
  - Interaction of FDI Stock and Human Capital 0.002** (0.001)
  - Interaction of FDI Stock and Public Capital 20.011 (0.014)
  - Countries 13
  - Observations 430
  - R-squared 0.93
- Asia-Pacific (column 3)
  - R&D Stock 0.023*** (0.005)
  - FDI Stock 0.096*** (0.013)
  - Imports 20.002** (0.001)
  - Financial Development 0.002** (0.001)
  - Interaction of FDI Stock and Public Capital 20.099** (0.044)
  - Countries 11
  - Observations 184
  - R-squared 0.95

### Notes on estimation
- white’s heteroscedasticity robust standard errors are in parentheses.
- Constants, country fixed effects, and year fixed effects are included but not reported.
- AEs 5 advanced economies; EMEs 5 emerging market economies; fdI 5 foreign direct investment; R&d 5 research and development.
- Significance: *p < .10; **p < .05; ***p < .01.
- source: IMf staff calculations.

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### Annex Table 3.2.4. Asia before and after the Global Financial Crisis

### Coefficients for two subperiods (Excludes Australia and New Zealand)
- 1980–2007
  - R&D Stock 0.010*** (0.003)
  - FDI Stock 0.127*** (0.014)
  - Imports 20.001 (0.001)
  - Financial Development 0.002** (0.001)
  - Interaction of FDI Stock and Human Capital 0.001 (0.001)
  - Countries 12
  - Observations 137
  - R-squared 0.97
- 2008–14
  - R&D Stock 0.090*** (0.027)
  - FDI Stock 0.107*** (0.027)
  - Imports 20.003*** (0.001)
  - Financial Development 0.001 (0.001)
  - Interaction of FDI Stock and Human Capital 0.002** (0.001)
  - Countries 11
  - Observations 66
  - R-squared 0.98

### Notes on estimation
- white’s heteroscedasticity robust standard errors are in parentheses.
- Constants, country fixed effects, and year fixed effects are included but not reported.
- Excludes Australia and New Zealand. AEs 5 advanced economies; A-P 5 Asia-Pacific; EMEs 5 emerging market economies; fdI 5 foreign direct investment; R&d 5 research and development.
- Significance: *p < .10; **p < .05; ***p < .01.
- source: IMf staff calculations.

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### Annex Table 3.2.5. Complementarity between Domestic Investment and Foreign Direct Investment in Emerging and Developing Asia and the Pacific

### Regression coefficients and statistics by subperiod
- 1978–2015
  - Lagged Investment 0.690*** (0.036)
  - Inward FDI Flows 0.133** (0.060)
  - Lagged Real Growth 0.156** (0.072)
  - Interest Rate 0.038** (0.016)
  - Observations 470
  - R-squared 0.84
- 1992–2015
  - Lagged Investment 0.664*** (0.041)
  - Inward FDI Flows 0.126* (0.065)
  - Lagged Real Growth 0.107 (0.084)
  - Interest Rate 0.036** (0.017)
  - Observations 382
  - R-squared 0.83
- 1997–2015
  - Lagged Investment 0.571*** (0.046)
  - Inward FDI Flows 0.146** (0.069)
  - Lagged Real Growth 0.129 (0.089)
  - Interest Rate 0.194** (0.088)
  - Observations 330
  - R-squared 0.82
- 2001–15
  - Lagged Investment 0.557*** (0.055)
  - Inward FDI Flows 0.170*** (0.077)
  - Lagged Real Growth 0.111 (0.104)
  - Interest Rate 20.046 (0.182)
  - Observations 273
  - R-squared 0.81
- 2008–15
  - Lagged Investment 0.325*** (0.078)
  - Inward FDI Flows 0.566*** (0.122)
  - Lagged Real Growth 0.144 (0.195)
  - Interest Rate 20.507 (0.361)
  - Observations 147
  - R-squared 0.83

### Notes on estimation
- standard errors are in parentheses.
- Constants, country fixed effects, and year fixed effects are included but not reported.
- Excludes Australia and New Zealand. fdI 5 foreign direct investment.
- Significance: *p < .10; **p < .05; ***p < .01.
- source: IMf staff calculations.

*source: IMf staff calculations.*

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_Source: https://www.imf.org/-/media/files/publications/reo/apd/2017/areo0517c3.pdf_