---
type: paper
slug: eunhee-kim-2023-state-intervention-innovation
title: >-
  Can innovation be induced by state involvement in the market? Evidence within
  an expanded framework of Hall & Soskice (2001)
authors:
  - '[[eunhee-kim]]'
  - '[[yeonbaekim]]'
year: 2023
venue: '[[structural-change-and-economic-dynamics]]'
volume: '66'
pages: 264-284
doi: 10.1016/j.strueco.2023.05.004
categories:
  - '[[macroeconomics]]'
  - '[[innovation-economics]]'
methods:
  - '[[fmols]]'
  - '[[dols]]'
  - '[[panel-cointegration]]'
  - '[[principal-component-analysis]]'
  - '[[institutional-complementarity-interaction]]'
  - '[[panel-fixed-effects]]'
themes:
  - '[[varieties-of-capitalism]]'
  - '[[state-capitalism]]'
  - '[[radical-vs-incremental-innovation]]'
  - '[[institutional-complementarities]]'
  - '[[patent-quality]]'
  - '[[revealed-comparative-advantage]]'
aliases: []
last_updated: '2026-05-20T01:41:32+09:00'
---
# Can innovation be induced by state involvement in the market? Evidence within an expanded framework of Hall & Soskice (2001)

*[[eunhee-kim]], [[yeonbaekim]] (2023)* · [[structural-change-and-economic-dynamics]] 66:264-284 · [DOI ↗](https://doi.org/10.1016/j.strueco.2023.05.004)

> [[eunhee-kim-2021-hall-soskice-state-role]] (EAP 2021) 의 *expanded VoC (LME, CME, SME)* framework 를 *innovation* 차원으로 확장. 29 OECD/선진국 × 1998-2017 panel (T=20) 의 [[principal-component-analysis]] 로 C_factor (corporate governance), L_factor (labor relations), S_factor (state involvement) 의 3-축 구성 후 *35 patent technology field* + *high/medium-high/medium-low tech RCA* 의 *technology-specific* 추정. 결과: state involvement 가 #7 IT methods for management (S β=0.0713 → 0.2643**), #4 Digital communication, #6 Computer technology 등 *strategic technology* 에서 *patent quality 향상*. *Institutional complementarity (L×S interaction)* 가 *대부분 technology field 에서 양 유의* — labor protection + state involvement 의 *combined effect* 가 single channel 보다 큼. 무역 차원에서 RCA in medium-high tech 가 *cointegrated* (Pt=-12.59**), RCA in medium-low tech 도 (Pt=-13.85***).

- **RQ**: Hall-Soskice (2001) 의 *CME = incremental, LME = radical* binary 명제가 *technology field 별* 로 성립하는가? *3rd type SME* 의 *innovation pattern* + state involvement 의 *radical vs incremental* differential effect 는?
- **방법론**: [[fmols]] / [[dols]] [[panel-cointegration]] ([[eunhee-kim-2021-hall-soskice-state-role]] 와 동일 framework), [[institutional-complementarity-interaction]] (C×S, L×S, C×L) 추가, 35 patent technology field (digital comm / computer / IT / bio / micro-nano / machine tools / engines / mechanical / transport 등) + RCA (high/medium-high/medium-low tech), patent quality index + patent count/GDP dual outcome
- **데이터**: 29 OECD + selected 국 × 1998-2017 (T=20), patent: WIPO/EPO 35 IPC field, 무역: RCA at 3 tech intensity level, 통제: globalization, IPR, ln GDP, ln Pop, inflation, R&D, education, defense
- **주요 발견**: (1) **Strategic technology field 에서 state involvement positive**: #7 IT methods β_S=0.2643** (complementary model), #6 Computer −0.0387* (base) → +0.0995 (complementary), #4 Digital comm S×C=−0.0939*, L×S=+0.1125** — *3-축 interaction 유의*. (2) **L×S complementarity 의 universal positive**: Table G.5 summary 에서 *35 fields 중 25+ field 에서 L×S 양 유의* (patent count/GDP). (3) **Incremental field (machine tools, engines)**: S_factor base β=-0.0623** → complementary β=+0.0561 — *interaction 추가 시 부호 반전*. (4) **무역 (RCA medium-high tech)**: Pedroni Pt=-12.59*, cointegrated. **RCA medium-low tech**: Pt=-13.85*** — state involvement 가 *기존 산업의 RCA* 도 induce. (5) #15 Biotech: S_factor β=+0.0077 (n.s.) → complementary β=-0.0117 — *biotech 는 state-driven 미흡*
- **시사점**: (a) Hall-Soskice 의 *binary 가설* 의 부분 반박 — state involvement + labor protection 의 *complementarity* 가 *radical innovation* 도 가능. (b) Korean *developmental state* 의 *strategic technology* 영역 (반도체, 배터리, AI) 의 *국가 R&D + 시장 결합* 모델의 정량 정당화. (c) 한계: small panel (29국), C/L/S factor 의 *measurement complexity*, complementary model 의 *3-way interaction* 의 추정 정밀도

![29 국의 *3-axis VoC* (C_factor corporate governance, L_factor labor relations, S_factor state involvement) 의 3D cluster map. Hall-Soskice (2001) 의 LME + CME 이분법 외 *SME (State-permeated Market Economy) 의 3rd cluster* 의 empirical separation 시각화](/papers/202309_KimEH_Can_innovation_be_induced_by_state_involvement_in_the_market_Evidence_within_an_expanded_framework_of_Hall_Soskice_2001/fig2.cropped.png)

## 요약

[[eunhee-kim-2021-hall-soskice-state-role]] (EAP 2021) 의 *expanded VoC + economic growth* 분석 의 *innovation 차원 확장* — 같은 first-author EunHee Kim, 같은 framework, dependent variable 만 patent quality index + RCA 로 변경. [[yeonbaekim]] author page 의 *제3기 (2018-2025) 의 *국가-시장 관계 + 혁신 제도* 라인의 capstone* (author page 분류). 기존 VoC-innovation 문헌 (Akkermans-Castaldi-Los 2009 Research Policy, Witt-Jackson 2016 J Int Bus Stud, Hall-Soskice 2001) 의 *LME = radical / CME = incremental* binary 의 *empirical 반박* + *state involvement 의 radical 가능성* 식별.

방법론은 4-stage. (i) [[principal-component-analysis]] 로 C_factor (corporate governance flexibility, financial system), L_factor (employment protection, collective bargaining), S_factor (state ownership, regulation depth) 구성. (ii) Hierarchical clustering 으로 LME / CME / SME 3-cluster (Korea, Norway, Greece 등이 SME). (iii) [[panel-cointegration]] test (Pedroni Gt, Ga, Pt, Pa) — radical innovation outcome (patent quality index) 에서 Pt=-14.28** (radicalness), Pt=-3.22 (backward citation). (iv) [[fmols]] + [[dols]] long-run estimation with C, L, S linear terms + L² + C×S, L×S, C×L *complementarity interactions*. 35 patent technology field × 2 outcome (quality index, count/GDP) × 2 spec (base, complementary) 의 grid 로 *field-specific differential effect* 추출.

핵심 정량 결과: *Table G.5 summary* 에서 patent count/GDP outcome 의 *L×S interaction* 이 35 field 중 25+ field 에서 *양 유의* — labor protection + state involvement 의 *combined effect* 가 *single channel* 보다 systematically 크다는 evidence. Strategic technology field 의 detail: (a) #7 IT methods for management: S_factor base β=0.0713* → complementary β=0.2643** (3.7배 증가); (b) #4 Digital communication: C_factor base −0.0209 → complementary +0.0995, C×S=−0.0939*, L×S=+0.1125** — *3-way interaction 유의*; (c) #6 Computer technology: C_factor 부호 반전 (−0.0387* → −0.0034); (d) #15 Biotech: S_factor β=+0.0077 (n.s.) → complementary β=-0.0117 — biotech 는 state-driven 미흡, *L_factor* 가 0.0652** 로 더 important. Incremental field (#26 machine tools): S_factor base β=-0.0623** → complementary +0.0561 — *interaction 추가 시 부호 반전*, L×S=−0.1807*** 의 negative 가 net effect 결정. 무역 (RCA medium-high tech): Pt=-12.59*, cointegrated. RCA medium-low tech: Pt=-13.85*** — state involvement 가 *기존 산업의 RCA* 까지 induce.

이 결과는 Hall-Soskice 의 *binary 가설* 의 partial 반박: (i) State involvement 가 *radical innovation field* (digital comm, IT methods, computer) 에서 *quality 양의 효과*, (ii) Labor protection + state involvement 의 *complementarity* 가 *대부분 technology field 에서 universal positive*, (iii) Bank-based corporate governance (C_factor) 가 *radical innovation 의 일부 field 에 양* — *bank-based = incremental only* 명제도 부분 반박. 정책 함의: Korean *developmental state* 의 *strategic technology* (반도체, 배터리, AI) 의 *국가 R&D + 시장 결합* 모델의 정량 정당화. *Picking winner* risk 보다 *enabling ecosystem* 의 *3-axis institutional complementarity* 활용이 핵심. 한계: (i) small panel (n=29 × T=20 = 580 obs), (ii) Complementary model 의 *3-way interaction* 의 추정 정밀도 (multicollinearity), (iii) Reverse causality (state involvement 의 *crisis response endogeneity*), (iv) 1998-2017 의 single VoC era.

## 핵심 결과

**Cointegration test (radical innovation outcomes, Pedroni)**

| Dependent | Gt | Ga | Pt | Pa |
|---|---:|---:|---:|---:|
| Radicalness | -2.34* | 4.17 | **-12.91***** | -4.95 |
| Backward citations | -6.92*** | -0.10 | -3.22 | -0.27 |
| RCA in high tech | -2.54* | -3.37 | -11.04 | -3.32 |
| **RCA in medium-high tech** | -2.91*** | -3.13 | **-12.59*** | -3.11 |
| **RCA in medium-low tech** | -2.96*** | -4.52 | **-13.85*****| -3.41 |

**Strategic radical technology field (patent quality index outcome)**

| Field | C_factor | L_factor | S_factor | C×S | L×S |
|---|---:|---:|---:|---:|---:|
| #4 Digital communication (comp.) | +0.099 | -0.100 | +0.044 | **-0.094*** | **+0.113*** |
| #6 Computer (base) | **-0.039*** | +0.111*** | -0.019 | — | — |
| **#7 IT methods (comp.)** | +0.082 | +0.250 | **+0.264*** | -0.091 | -0.030 |
| #15 Biotech (base) | -0.023 | **+0.065*** | +0.008 | — | — |
| #22 Micro/Nano (base) | **+0.171*** | **+0.284*** | +0.094 | — | — |

**Incremental field (sign reversal pattern, patent quality)**

| Field | Spec | S_factor | L×S |
|---|---|---:|---:|
| #26 Machine tools | Base | **-0.062*** | — |
| #26 Machine tools | Complementary | +0.056 | **-0.181*** |
| #27 Engines/pumps/turbines (comp.) | | +0.056 | **+0.112*** |
| #30 Thermal (comp.) | | -0.053 | **-0.130*** |
| #32 Transport (comp.) | | **+0.126*** | **-0.056*** |

> **정량 결론** (i) Strategic radical technology 의 S_factor positive 가 *complementary model* 에서 강화 — *L×S, C×S interaction* 통해. (ii) *Field-specific differential* — biotech 는 L_factor 주도, IT methods 는 S_factor 주도, micro-nano 는 C×L 주도. (iii) Incremental field 에서 *interaction 추가 시 부호 반전* — *base model alone 은 misleading*.

## 방법론 노트

핵심 추정 식은 *base model* (single-channel) 과 *complementary model* (3-way interaction) 의 paired 비교:

$$
\text{Innovation}_{it} = \alpha + \beta_C C_{it} + \beta_L L_{it} + \beta_S S_{it} + \gamma' X_{it} + u_{it} \quad \text{(base)}
$$

$$
\text{Innovation}_{it} = \alpha + \beta_C C + \beta_L L + \beta_S S + \beta_{CS}(C \times S) + \beta_{LS}(L \times S) + \beta_{CL}(C \times L) + \gamma' X_{it} + u_{it} \quad \text{(complementary)}
$$

여기서 $X$ = (globalization index, IPR strength, ln GDP, ln population, inflation, R&D/GDP, education, defense spending). Outcome 은 (i) patent quality index (radicalness, backward citation 등 4 measures), (ii) patent count/GDP, (iii) RCA at 3 tech intensity levels. [[fmols]] (Fully Modified OLS, Pedroni 2001) 과 [[dols]] (Dynamic OLS, Stock-Watson 1993) 의 *long-run cointegration coefficient* 가 핵심 — *serial correlation + endogeneity 자동 보정*. 식별 가정: (i) Panel cointegration 의 *long-run equilibrium*, (ii) C/L/S factor 의 *exogeneity* (PCA 후 standardized), (iii) Interaction term 의 *meaningful multicollinearity 범위* (mean-centered).

*Identification 핵심*: Base vs complementary spec 의 *paired 비교* 가 *institutional complementarity hypothesis* (Hall-Gingerich 2009) 의 핵심 검정. Base model 만 보면 S_factor 의 negative effect 가 *machine tools* 에서 관찰되지만, complementary model 추가 시 *L×S interaction* 이 main negative source — 즉 S 자체가 아닌 *L 과의 상호작용* 이 incremental field 의 driver.

## 연구 계보

[[yeonbaekim]] author page 의 *제3기 (2018-2025) 국가-시장 관계 + 혁신 제도 라인의 capstone* (author page 분류). 직접 predecessor 는 [[eunhee-kim-2021-hall-soskice-state-role]] (EAP 2021 72:530-548) — *expanded VoC framework 의 economic growth* 분석 — 의 *innovation 차원* 후속. 같은 first author, 같은 PCA + cointegration framework, dependent variable 만 변경. Sibling: [[changhyeon-song-2020-socio-cultural-tea]] (Tech in Society 2020) 의 *welfare-entrepreneurship* 의 *macro VoC* 통합 라인. 이론적 뿌리: (a) Hall & Soskice (2001) *Varieties of Capitalism* — LME/CME 이분법 정초, (b) Hall & Gingerich (2009) BJPS 의 *institutional complementarity*, (c) Amable (2003) *Diversity of Modern Capitalism*, (d) Schneider (2009), Nölke-Vliegenthart (2009), Nölke-ten Brink-Claar-May (2019) 의 *State-Permeated Market Economy*, (e) Akkermans-Castaldi-Los (2009) Research Policy 의 *VoC-innovation pattern* 실증 라인, (f) Witt & Jackson (2016) J Int Bus Stud 의 *VoC + innovation 메타-비판*, (g) Pedroni (2001) ReStat, Stock & Watson (1993) Econometrica 의 *FMOLS/DOLS* 계량. RCA 측정: (h) Balassa (1965) 의 *revealed comparative advantage* 정의, patent quality: (i) Lanjouw & Schankerman (2004) Econ J 의 *patent quality index*.

## See also

- [[yeonbaekim]]
- [[eunhee-kim]]
- [[fmols]]
- [[dols]]
- [[panel-cointegration]]
- [[principal-component-analysis]]
- [[institutional-complementarity-interaction]]
- [[varieties-of-capitalism]]
- [[state-capitalism]]
- [[radical-vs-incremental-innovation]]
- [[institutional-complementarities]]
- [[patent-quality]]
- [[revealed-comparative-advantage]]
- [[eunhee-kim-2021-hall-soskice-state-role]]
- [[structural-change-and-economic-dynamics]]
- [[changhyeon-song-2020-socio-cultural-tea]]