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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract. The transformation of China into a knowledge based economy is currently one of the most intensively debated research issues in Economic Geography and Regional Science. The focus of this study is on the effects of knowledge production and knowledge spillovers on manufacturing total factor productivity (TFP) in Chinaat the level of Chinese regions -through the lens of the regional knowledge capital model (KCM). The objective is to estimate the impact of region-internal and regionexternal knowledge capital on TFP in manufacturing industries across Chinese regions, and, by this, providing evidence on the crucial question whether TFP in China is increasingly based on knowledge production and diffusion. Relying on the regional KCM as theoretical framework, we derive a Spatial Durbin Model (SDM) relationship that can be used for empirical testing. The Chinese coverage is achieved by using regional data on 29 Chinese provinces for the years 1988-2007. The dependent variable denotes regional TFP, describing how efficiently each province transforms physical capital and labour into gross value added in manufacturing industries. We explain TFP -starting from the regional KCM -by region-internal and regionexternal knowledge stocks, the latter referred to as the inter-regional knowledge spillover pool. We measure regional knowledge stocks in terms of patents granted by the Chinese patent office. In estimating the effects, we implement a panel version of the standard SDM that controls for spatial autocorrelation as well as individual heterogeneity across regions. The specification incorporates a spatial lag of the dependent variable as well as spatial lags of the independent variables, allowing for the endogenous estimation of TFP effects resulting from region-external knowledge stocks. In order to identify the point in time of China shifting towards a knowledgebased economy, we employ a panel LM unit root test, providing empirical evidence for structural breaks in the time dimension of the data. By this, the study has the potential to break new ground in providing systematic statistical evidence on the transformation of China into a knowledge-based economy. Terms of use: Documents in

This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. | ECO/WKP(2021)20Unclassified OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the author(s).Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works.

This paper was approved and declassified by written procedure by the Committee for Scientific and Technological Policy (CSTP) on 15 September 2019 and prepared for publication by the OECD Secretariat. Note to Delegations: This document is also available on ONE M&P under the reference code: DSTI/STP/TIP(2019)12/FINAL This document, as well as any data and any map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.