Silviase/jgov_v1.4_full_ann huggingface dataset:
格統一リユースびんを使用した約200アイテムの商品を扱っています。一つのびんが何度も洗浄されて使用されるため、例えばジュースに使われた容器が、次はお酢の容器として使われることもあります。北海道や九州までの広域的な地域内において、五つの生協団体に加盟する合計約210万世帯が、県や地域を限定せずにびんのリユースを行っています。

規格統一リユースびんの底や肩部には、リターナブルびんの頭文字である「Rマーク」が刻印されており、「Rびん」と呼ばれています。規格を統一したびんを使うことで、リユースに不可欠な回収、洗浄、選別といった作業の効率性を高めています。さらに、生協組合員が共同購入する際の配達ルートを活用して、使用済みのびんの回収を行っています。こうした取組は、びんを作るメーカー、内容物を充填する提携生産者、回収や洗びんの事業者と生協といった複数の関係者が協働することで実現しています。「びん再使用ネットワーク」は、平成6年の設立以来、約1億8,335万本のびんを回収してきており（回収率約67%）、回収したRびんの累積量をCO₂の削減量に換算すると、約6万655トン（東京ドーム約25個分）となります。

加えて、使用本数の多い900mlと500mlのびんについては、びんの外側表面に樹脂を薄くコーティングし、ガラスを薄くしても強度を保つ加工を行うことで、従来のリユースびんに比べびんの重量を約40%軽くした「超軽量リユースびん」を採用しています。従来のリターナブルびんと超軽量R

従来
びん	超軽量
びん	比較した場合の、
超軽量びんの特徴
重量(g/本)	320	195	約40%軽量化
CO₂排出量(g/本)
(製造から廃棄までのライフ
サイクルにおいて、回収率
75%とした場合の排出量)	121	91	約25%削減
再使用可能回数(回)	35	50以上	70%以上向上
洗びん時のロス率(%)	2.6	0.25	約1/10に低減

資料：びん再使用ネットワーク

びんを比較してみると、重量、CO₂の削減効果、強度、洗びんロス率（洗浄による破損発生率）が改善されており、より環境負荷が低いことから、長距離輸送を伴う広域での再使用に適しています。

「びん再使用ネットワーク」に加盟する五つの生協団体により、北海道や九州までの広域的な地域内で同じ規格のびんが効率的にリユースされることで、生協ごとの地域循環圏が構築されており、環境負荷の低い資源循環を実現しています。

## 4 第32回オリンピック競技東京大会・第16回パラリンピック競技東京大会を契機とした都市づくり

2020年東京大会が開催される平成32年（2020年）は、我が国の温室効果ガスの削減目標年であり、かつ、2020年以降の新たな国際的枠組みの開始年になる予定の年であるとともに、平成22年に名古屋で開催された生物多様性条約第10回締約国会議（COP10）において採択された「愛知目標」の短期目標（生物多様性の損失を止めるために効果的かつ緊急な行動を実施する）の目標年でもあります。このような大きな節目の年に開催される2020年東京大会は、我が国の環境配慮への姿勢が世界中から注目される大会になると考えられます。そのため、オリンピックを通じ、我が国が環境問題の解決に向けた道筋を世界に先駆けて示していくことが重要です。また、これらの解決のためには、技術やインフラを導入するだけでなく、本大会を契機として、環境に係る諸課題を抱える東京をより住みよい都市にすることで、社会の仕組みや人々の価値観を変え、「循環共生型社会」を実現していくことが必要です。
このような考え方に基づき、環境省では、平成26年8月に「2020年オリンピック・パラリンピック東京大会を契機とした環境配慮の推進について」を取りまとめるとともに、これに基づく取組を推進することとしています。そうした地方の環境、経済、社会の統合的向上に向けた動きとして、以下ではオリンピックを契機とした環境配慮に関する都市づくりの取組を紹介していきます。

## (1) 「環境にやさしい五輪」及び「環境都市東京」の実現

東京都市圏（ここでは、東京都、千葉県、埼玉県及び神奈川県とする。）について、その経済規模を見てみると、平成22年度（2010年度）の域内総生産額が合計1兆8340億ドル（平成22年度支出官レート：1ドル=94円で換算して、172兆3,960億円）と、日本全体のGDPの約1/3、G7諸国のイタリア、カナダのGDPに匹敵する世界最大の都市圏です。また、一人当たり総生産も米国やカナダより多い5万1,510ドル（同484万1,940円）となっています（図3-2-30）。このように、東京都市圏での様々な取組は、金額ベースで主要国一国の取組に相当するものであり、東京都市圏における「循環共生型社会」の構築に向けた取組を内外に示すことで、世界の取組を加速させることが期待されます。

図3-2-30 主要各国と東京都市圏の国内（域内） 総生産及び一人当たり総生産

注：2010年（平成22年）データ。東京都市圏のみ2010年度（平成22年度）。資料：内閣府「県民経済計算」及びIMF「World Economic Outlook」より作成

## (2) 「環境にやさしい五輪」及び「環境都市東京」の実現に向けた取組

2020年東京大会の立候補ファイルでは、廃棄物抑制、環境負荷の少ない輸送の実施等、環境面での積極的な対応が公約されています。こうした点も踏まえ、大会自体の環境負荷の低減と、大会を契機とした我が国の環境配慮の推進に向けて、東京都・民間事業者、公益財団法人東京オリンピック・パラリンピック競技大会組織委員会（以下「大会組織委員会」という。）等の大会関係者の取組を推進するため、政府が当面取り組んでいくべき事項として、低炭素化の推進、ヒートアイランド対策の推進、良好な大気・水環境の実現、リデュース・リユース・リサイクル（3R）の徹底、環境情報の発信等があります。

## ア 低炭素化の推進

2020年東京大会が開催される平成32年は、既述のとおり温室効果ガスの削減目標年（平成17年度比3.8%減）であることから、大会関連施設の建設から廃棄に至るまでの全プロセスでの低炭素化、大会開催時の選手・観客の移動手段の低炭素化等について、大会組織委員会等に積極的に促していく必要があります。

また、大会会場である東京都市圏の低炭素化を特に図ることが重要であることから、国は、低炭素化技術の普及・波及効果に関する東京都市圏全体での予測シミュレーションの実施、電気自動車（EV）や燃料電池車（FCV）とその充電ステーションや水素ステーションの普及及びこれらに係る技術開発、高効率の熱供給システム等の省エネルギーに関する技術の活用支援等を行うことが必要です。

さらに、オリンピックを契機に地方の活性化を促すため、今後開発されるオリンピック・パラリンピック
関連商品・サービスについて、全国各地で創出されるカーボン・オフセットの活用を促進することも重要です。

加えて、ロンドンオリンピックでは、環境負荷の低い物品を調達する「グリーン購入」が徹底されなかったと評価されたことも踏まえ、2020年東京大会では、グリーン購入について一層の展開を図るため、事業者等の関係者による現行基準よりも厳しい購入基準の自主的採用を促すとともに、国が技術的支援等を行う必要があります。

また、東京のエネルギーの需要密度は現在、北海道や東北等の約50～60倍となっており、将来においても、東京に存在する再生可能エネルギーによって東京のエネルギーを賄うことは難しいと考えられます。そのため、前項で示したように、大会を契機として、再生可能エネルギーのポテンシャルが多い地域から再生可能エネルギーを調達していくことも考えられます。東京の代表的な街区に全国各地から再生可能エネルギーが供給されるといった地域間連携を行うことで、資金が都市から地方に流れるとともに、東日本大震災の被災地を始めとする地方における雇用創出や経済活性化につなげることが期待できます。

## イヒートアイランド対策の推進、良好な大気・水環境の実現

## （ア）ヒートアイランド対策

過去100年で、東京の平均気温は約3℃、第18回東京大会が開催された昭和39年頃と比べても平均で1℃以上の上昇となっています。中小都市の過去100年の平均気温の上昇が約1℃であることを鑑みると、ヒートアイランド現象による東京の平均気温の上昇幅は極めて大きいと言えます。ヒートアイランド現象の発生要因としては、主にエアコンや自動車等の人工排熱の増加、緑地や水面の減少、地表面の舗装等による人工被覆の増加、高層建築物による天空率の低下（図3-2-31）などが挙げられます。

2020年東京大会が真夏に開催されることを鑑みると、選手が最大限の力を発揮できるよう、ヒートアイランド現象への対策を推進していく必要があります。具体的には、大会後の対策の継続も見据え、大会会場やコース周辺等の保水性・透水性舗装等の設置（図3-2-32）、低炭素化の取組も兼ねた、高効率の空調機器等の導入による人工排熱の低減、緑地や水面の確保など、選手や観客等への暑さによるストレス（以下「暑熱ストレス」という。）の軽減策を講じていく必要があります。

図3-2-31 天空率と放射の関係

資料：環境省

図3-2-32 保水性・透水性舗装のイメージ図

資料：環境省

## （イ）熱中症対策

前述のヒートアイランド対策に併せて、今後増加が見込まれる日本の夏の暑さに慣れていない外国人観光客に対して、暑熱ストレスを軽減するための情報提供も必要です。具体的には、大会会場ごとの暑さ情報等の発信やリーフレット等の多言語化による普及啓発により、日中の炎天下の暑さの度合いや熱中症の知識に関する情報の提供を行っていくこと等が考えられます。

## （ウ）大気汚染対策

2020年東京大会の開催に当たっては、良好な大気環境が市民のみならず選手や観客に対し提供されることが重要です。そのため、東京都及び周辺地方公共団体と連携して、光化学オキシダントの原因物質である
$ NO_{x} $ の排出規制等、濃度低減対策を進めていく必要があります。

## （エ）東京湾等の水質改善

2020年東京大会は、閉鎖性の内湾である東京湾岸の臨海部が主要会場であり、トライアスロン等、東京湾そのものを利用する競技も予定されています。また、都心の貴重な水辺空間である皇居外苑濠（内濠）の周辺等では、マラソン競技など多数の競技が予定されているものの、水の滞留と継続的な汚濁物質の流入等によってアオコが大量発生するなど、悪臭や景観面での悪影響が懸念されます。水質環境の改善に向け、関係省庁や地方公共団体と連携し、水質浄化に向けた取組を進める必要があります。

## ウ 3Rの徹底等

2020年東京大会では、大会関連施設において、3Rに関する技術開発や実証事業を実施するとともに、食品ロスの削減やドーピング検査に使用する注射針等の円滑な処理等を含めた各種の対策を進めていく必要があります。また、東京都市圏における取組として、2R（リデュース及びリユース）を推進するとともに、その上で発生する廃棄物については、リサイクル促進のために統一分別ラベルを導入し、外国人も含む観客等の自発的な分別行動を促進することが必要です。

## エ 我が国からの環境情報の発信等

我が国が環境先進国であることを国内外に広くPRするため、日本の環境技術や制度の紹介を始め、参加型のESDイベント等の開催等、2020年東京大会に向けての取組を効果的に発信していく必要があります。

また、大会を契機に、日本を訪れる観光客や海外メディアに対し、東日本大震災から復興した姿を積極的に発信していくことも重要です。加えて、開催地である東京都が擁する多摩地域西部や伊豆諸島、小笠原諸島等国立公園や世界自然遺産地域等はもとより、全国各地の国立公園についての海外への積極的な情報発信を行うとともに、東京大会を機に日本を訪れる外国人旅行者の地方への誘客を図ることで、大会を契機とした地方の活性化を図っていくことが期待されます。
ESRI Discussion Paper Series No.54

Quality of Child Care in Japan: Evidence from Micro-level Data

by

Haruko Noguchi and Satoshi Shimizutani

August 2003

Economic and Social Research Institute

Cabinet Office

Tokyo, Japan
Quality of Child Care in Japan:

Evidence from Micro-level Data $ ^{1} $

Haruko Noguchi and Satoshi Shimizutani $ ^{2} $

August 2003
## Abstract

This study is a comprehensive empirical assessment on the quality of child care in Japan. Since no single index is entitled to stand for the quality of child care, we adopt three different approaches to measure quality. We take advantage of some unique survey data, which contains the largest sample size and the highest quality currently available in Japan.

The “test score” approach uses several indexes to evaluate the quality and to compare the total scores by different management. We observe that child care centers operated by different types of managements have advantages in different aspects; a specific type of management does not get the highest score in all detailed evaluations.

The “quality of workers” approach adjusts for the non-random allocation of workers to measure the quality of child care closely related with the quality of employees. The results based on the treatment effect model demonstrate that the share of regular or qualified workers and the number of children per worker is better in private-licensed centers than it is in public centers, and thus provide higher quality of services than do the public centers.

The “users’ request” approach utilizes the survey on child care users for evaluating the services currently being offered and demanded in future. Our findings are consistent with the “quality of workers” approach in that the quality is better in private-licensed centers regarding parents’ convenience and additional care such as extended care and education for children.

These results demonstrate that private licensed centers are more likely to provide higher quality of services than public centers.
### 1. Introduction

Measuring the quality of child care is fundamental for evaluating the output in the child care industry. Due to asymmetry of information, care users cannot choose facilities without appropriate information on the quality of care. Recently, there has been growing public interest and demand for disclosure of information on the quality of care due to many unfortunate accidents and awareness of unfairness in services between licensed and non-licensed centers $ ^{3} $ .

Quality evaluation matters not only for providing information of care and for assuring children's safety. It also creates appropriate references in measuring the efficiency of management in the child care industry. Japanese households in urban areas suffer from a severe undersupply of child care, and higher wage costs are alleged to be the cause of the bottleneck (Noguchi Shimizutani and Suzuki (2003)). However, whether input costs are higher should depend on the quality of output. In other words, there might be room for higher costs, which might be justified by higher quality of care.

This study provides a comprehensive empirical assessment on the quality of child care in Japan. Quality measurement is critical but at the same time is a heavily disputed topic. The main reason is that there is neither a unique quality index nor a consensus on what stands for better quality of care.

Therefore, this study will adopt three different ways to evaluate quality, rather than relying on a single index. Concretely, we take the following measures: “test score” and “quality of workers” approaches as supply-side measures, and the “users’ request” approach as a demand-side measure.

The “test score” approach is similar to that taken in a previous U.S. study (Mocan (1995)). This approach classifies various service items associated with user’s benefits into several categories. In this study, we adopt 40 detailed items classified into four categories indicating each facility’s characteristics. The scoring methods, based on a simple average or principal scores, are very straightforward and most commonly used.

However, some critics might object to the fact that the choice of concrete items depends on each researcher and thus could be biased. Thus, we adopt the second method
called the “quality of workers” approach. The basic strategy is to examine the difference in several objective measures associated with quality of workers by types of management. We utilize the treatment effect model to examine the difference in some “quality” variables including the ratio of regular workers and the stability of workers.

The third method, on the contrary, is to use information on child care users which could be called the “user’s request” approach. Concretely, we utilize users’ evaluations on the currently provided services and requested demands for quality of care.

To address these issues, we take advantage of our unique survey on child care suppliers and demanders. Our data set contains an unusually large and high-quality data and is, as far as we know, the best available in Japan.

We preview our empirical results. First, the “test score” approach demonstrates that a specific type of management does not get the highest scores in all detailed evaluation aspects. Second, the “quality of workers” approach observes that the shares of regular or qualified workers and the number of children per worker are better in private licensed than public centers. Third, in the “users’ request” approach, the quality is better in private licensed centers than it is in public centers regarding parents’ convenience. These results show that private-licensed centers are more likely to provide higher quality of services than public centers.

This paper is organized as follows. Section 2 provides a literature review on the quality of child care mainly in the United States. Section 3 describes two data sets used in this study. Section 4 performs the “test score” approach to measure quality. Section 5 compares the quality of workers among different types of management using the “treatment effect” approach. Section 6 employs the “users’ requests” approach. Section 7 discusses the results from these three strategies, and the final section concludes.

### 2. Literature Review

In the United States, dozens of empirical studies have been conducted that compare the quality and efficiency of child care services $ ^{4} $ . Until the beginning of the 1990s, a
relatively simple index had been used as a proxy to measure quality of child care, such as ratio of qualified workers, employees' educational levels, years of experiences, equipment, and area per child (Chipty and Witte (1994), Mukerjee and Witte (1991), Mukerjee and Witte (1993)). These studies mainly focused on “inputs” to produce child care as quality measures, called a “structural index.”

However, recent studies emphasize some new quality measures developed by psychologists rather than the traditional “structural index.” Blau (1999), Blau and Mocan (2002) and Mocan (1995,1997) adopt these new “developmental psychological characteristics” measures to indicate interaction between children and child care workers and developmental environments for children. This type of index includes the Early Childhood Environmental Rating Scale (ECERS), the Infant/Toddler Environmental Rating Scale (ITERS), the Caregiver Interaction Scale (CIS), the Teacher Involvement Scale (TIS) and the UCLA Early Childhood Observation Form.

Contrary to the United States, Japan has few empirical studies on quality of child care, though that number has been growing recently. However, most of them are based on personal experiences or specific events, and it is hard to generalize them to measure the quality of care in the child care market as a whole. Also, they are not comparable with empirical works in the United States, using a rich micro-level data.

The Ministry of Health, Labor and Welfare (2001) provides the most comprehensive survey on objective evaluation of the quality of care. This report proposes that quality should be evaluated in four categories: (1) support for child’s development, (2) child care support for parents, (3) cooperation with residents and related organizations, and (4) soundness of management and operations. Shiraishi and Suzuki (2002, 2003) follow this criteria and choose 33 items to evaluate. They conclude that quality of child care is better in private-licensed facilities, followed by public-owned centers. However, their studies are seriously hampered by small samples (300 centers) with smaller variables in four limited prefectures. Shimizutani and Suzuki (2002) adopt the similar approach to the Japanese long-term care market.

This study is substantially different from these other studies in Japan. First, we adopt three different approaches to evaluate quality of care, where no consensus is attained. An evaluation based on a single approach might be biased, and robust results could not be obtained. Our study thus provides a whole picture on the quality of care, though it is
disputable, and clear policy implications could be drawn. Second, we take our best available data from suppliers and demanders in Japan described in the next section, while other studies are based on very limited small samples. Third, in the traditionally common “test score” approach, we re-categorize the items of variables to stand for quality so that they could be comparable with previous studies in the United States, including developmental psychological measures.

### 3. Data Description

We use two different data sets in this study. One is the supply-side survey on child care providers used for the “test score” and “quality of worker” approaches. The other is the demand-side survey on child care demanders for the “users’ requests” approach.

The supply-side analysis of this study is based on a unique survey on child care centers conducted by the Price Policy division of the Cabinet Office, Japanese government, in the summer of 2002. This data is, to our knowledge, the most comprehensive survey on child care workers with the largest sample size. We were able to perform the survey with special collaboration and deep understanding by local governments.

Before performing the survey, we visited several local governments, including Tokyo Prefecture, to ask their support in the survey. We explained the purpose of our research and consulted several important issues with officials in charge of child care policies at local governments, including detailed items covered in the questionnaire, and considered the feasibility of each question and preciseness of response.

The sample of the survey contains child care centers located in the entire 729 municipal areas of 10 prefectures around Tokyo: Chiba, Gunma, Ibaragi, Kanagawa, Nagano, Saitama, Shizuoka, Tochigi, Tokyo and Yamanashi Prefectures. Out of 729 districts, we collected data from the 533 local governments. The response rate of 73.1% is remarkably high. The figure would be even higher if we remove some local governments with no child care centers in the administrative region.

Local governments collaboratively to the survey provided rich and valuable information on child care facilities within the area, such as type of management, size, service contents, and equipment. Moreover, they collected detailed information on all workers in each facility from 20 percent of public centers and 40 percent of licensed private facilities by
individual local governments, which were randomly selected $ ^{5} $ . The sample size is 16,735 workers from 1,382 centers (7,102 workers from 687 public licensed centers and 9,633 workers from 695 licensed private centers).

In addition, we collected the same information from non-licensed facilities operating in Tokyo Prefecture. Non-licensed centers are concentrated in urban areas, where the child care supply is insufficient and where excess demand for care is observed. Note that all non-licensed child care centers are recognized by local governments. After eliminating the samples whose necessary data is missing, we ended up with 911 and 173 workers in 42 nonprofit and 21 for-profit centers, respectively.

On the demand-side, we also performed a survey on households with children younger than five years old in Chiba, Kanagawa, Saitama, and Tokyo Prefectures within 30 kilometers from the center of Tokyo. This survey was conducted from July to September 2002, the same period with the supply-side survey. The sample is 3,100 households with children who are younger than five years old, including both child care users and non-users. They were randomly chosen from household registrations. We received responses from 533 households using child care and from 1,020 not using child care centers.

### 4. The “Test Score” Approach

This section evaluates the quality of care based on the “test score” approach. Concretely, we use 40 detailed items to measure quality, which are categorized into (1) structural index, (2) developmental psychological index, (3) parents’ convenience index, and (4) other index, as below. Based on previous surveys conducted in the United States, we categorize closely related items as the developmental psychological index, including developmental circumstances, and child’s health and safety $ ^{6} $ .

A. Structural Characteristics (10 items)

(a) Child care workers’ characteristics
1. Share of qualified workers

2. Share of regular workers

3. Years of work experience

4. Provision of training program for first-year workers

5. Provision of outside training program

6. Provision of leadership training program

(b) Child care facilities’ characteristics

7. Area per child of special room for infants

8. Area per child of nursery room

9. Outside playground area (except public parks near the center as substitute)

10. Inside playground area

B. Developmental Psychological Characteristics (15 items)

(a) Developmental psychology

11. Field day

12. Excursions outside the center

13. Playing in small swimming pools

14. Special rhythm gymnastics for infants

15. Playing outdoors in parks

16. Education for children

(b) Children’s health and safety management

18. Health examinations for children

19. Accountability for accidents for parents

19. Accountability for accidents for parents

20. Communication notes between child care workers and parents

21. Meetings among care workers

22. Health examinations for care workers

23. Collaboration with medical facilities besides affiliated physicians

24. Insurance protection for any accidents or troubles related to children within the center

25. Safety video camera located in the nursery room or outside playground
C. Parent's Convenience Characteristics (10 items)

26. Distance to train station

27. Hours of operation

28. Hours of extensive child care

29. Provision of holiday care

30. Provision of post-acute care

31. Frequency of parents’ meetings on weekdays

32. Provision of parents’ meetings on holidays (Saturdays)

33. Provision of child care support or consulting

34. Provision of complaint processing system from parents

35. Communication through e-mail with parents

D. Other Characteristics (five items)

36. Provision of care for disabilities

37. Provision of emergent or temporary care

38. Availability for residents to use the garden on holidays

39. Provision of care for foreigners

40. Provision of websites

Based on these items, we calculate scores in four different ways. First, to calculate “small scores,” we add up individual items for the four sub-categories. If an item is an indicator variable, we allocate one point for any provision and zero for others. If an item is not measured zero or one, we allocate one point for those with more than average and zero otherwise. Second, we simply add up all 40 items from all sub-categories, called as the “total scores.” Third, we apply factor analysis to calculate the first principal component by sub-category, which is called as the “small principal scores.” Fourth, we calculate the first principal component for all 40 items, called as the “total principal scores.”

Table 1 reports the correlation coefficients between the “small scores” and “small principal scores” in each sub-category. Surprisingly, the coefficients are small. In addition, those between the structural index and other three types of indexes are very low. Therefore, we should note that the quality index measured by the traditional “structural” and
“developmental psychological” indexes could be very different.

In what follows, we use these measures to evaluate the quality of child care in different types of management. First, we will look at the aggregate index. Table 2 shows the “small scores.” Public centers have higher scores in the structural index than do private licensed or for-profit. On the contrary, private centers are advantageous in the developmental index or parents’ convenience. As a result, the “total scores” are higher for private facilities than for public centers.

On the other hand, Table 3 shows the results of the “small principal scores” to provide a slightly different picture. If we compare the public and private licensed centers, the results on the structural index and parents’ convenience are same with those in Table 2. The advantage for private licensed centers disappears in developmental psychological characteristics. The “total principal scores” maintain the results that quality of services in private centers is superior to that in public-owned centers. Private non-licensed facilities are advantageous in the structural index and parents’ convenience in Table 3.

We will investigate the difference in more detailed items. The results on the structural index are reported in Table 4. Public centers have better scores in skills or years of experience of child care workers. This is the case for the comparison between public and private non-licensed centers except the number of children per worker. Considering that the non-licensed centers in our study are relatively large to be entitled to receive subsidies, quality provided by public centers is in general superior to that of private facilities.

Table 5 reports the results of the developmental psychological index. Compared with the structural index, quality of service in public-owned centers is more equal with that in private licensed centers. Public centers are still more advantageous than for-profits are.

Furthermore, the result on the parent’s convenience characteristics in Table 6 demonstrates that private-licensed centers are much better than public facilities. These findings contrast with the results based on the structural index. Finally, Table 7 shows that private centers provide better quality than public facilities do, except care for those with disabilities.

We could conclude as follows. We observe that public centers are much more dominant in the structural index. The advantage of public centers becomes less clear in the developmental psychological measurements. Private-licensed centers are advantageous in parent’s convenience and other characteristics. Thus, we observe that one type of