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Recent years have witnessed significant progress in developing deep learning-based models for automated code completion. Although using source code in GitHub has been a common practice for training deep-learning-based models for code completion, it may induce some legal and ethical issues such as copyright infringement. In this paper, we investigate the legal and ethical issues of current neural code completion models by answering the following question: Is my code used to train your neural code completion model? To this end, we tailor a membership inference approach (termed CodeMI) that was originally crafted for classification tasks to a more challenging task of code completion. In particular, since the target code completion models perform as opaque black boxes, preventing access to their training data and parameters, we opt to train multiple shadow models to mimic their behavior. The acquired posteriors from these shadow models are subsequently employed to train a membership classifier. Subsequently, the membership classifier can be effectively employed to deduce the membership status of a given code sample based on the output of a target code completion model. We comprehensively evaluate the effectiveness of this adapted approach across a diverse array of neural code completion models, (i.e., LSTM-based, CodeGPT, CodeGen, and StarCoder). Experimental results reveal that the LSTM-based and CodeGPT models suffer the membership leakage issue, which can be easily detected by our proposed membership inference approach with an accuracy of 0.842, and 0.730, respectively. Interestingly, our experiments also show that the data membership of current large language models of code, e.g., CodeGen and StarCoder, is difficult to detect, leaving amper space for further improvement. Finally, we also try to explain the findings from the perspective of model memorization.

Special Issue, vol. 42, nr 1

Special Issue, vol. 56, nr 1

This book looks at the major policy challenges facing developing Asia and how the region sustains rapid economic growth to reduce multidimensional poverty through socially inclusive and environmentally sustainable measures. Asia is facing many challenges arising from population growth, rapid urbanization, provision of services, climate change and the need to redress declining growth after the global financial crisis. This book examines poverty and related issues and aims to advance the development of new tools and measurement of multidimensional poverty and poverty reduction policy analysis. The book covers a wide range of issues, including determinants and causes of poverty and its changes; consequences and impacts of poverty on human capital formation, growth and consumption; assessment of poverty strategies and policies; the role of government, NGOs and other institutions in poverty reduction; rural-urban migration and poverty; vulnerability to poverty; breakdown of poverty into chronic and transitory components; and a comparative study on poverty issues in Asia and other regions. The book will appeal to all those interested in economic development, resources, policies and economic welfare and growth.

How significantly inter-industry wage differentials contribute to rising income inequality is an essential policy issue for transitional economies. Using regression-based inequality decomposition, this paper finds that inter-industrial wage differentials contributed increasingly to income inequality in urban China through 1988, 1995, and 2002, mainly due to rapid income growth in monopolistic industries. Factors such as region, education, ownership, occupation, and holding a second job also contribute increasingly to income inequality, while being employed the whole year and age have decreasing contributions. If China seeks to reduce urban income inequality, removing entry barriers in the labor market and breaking monopoly power in the goods market are essential policy prescriptions., Fukino foundation

China has been running a large trade surplus with the rest of the world, particularly with the USA and EU. This has caused considerable diplomatic tensions and tremendous pressure on the Chinese currency. Existing analytical studies, however, mostly focus on real exchange rate and income as determinants of China's trade imbalances. Little attention has been given to the role of inflow and outflow of foreign direct investment (FDI). The purpose of this paper is to fill in this gap in the literature by adding FDI to China's trade balance model. Fitting aggregate annual data from 1979 to 2007 to SURE (Seemingly Unrelated Regression Equations) and later ARDL (Autoregressive Distributed Lags) models, we find that although outflow FDI does not play an important role in determining Chinese trade flows and trade balance, inflow FDI contribute significantly to Chinese exports and thus its trade surplus with the rest of the world. Interestingly, devaluation of the Chinese currency Yuan is found not to affect Chinese trade balance. We also find that both Chinese income and the income of the world play important roles in Chinese trade imbalance. Finally, we find that Chinese trade imbalance is stable.

This paper depicts the trend of regional inequality in rural China for the period 1985-2002. The total inequality is decomposed into the so-called within- and between-components when China is divided into three regional belts (east, central and west). A regression-based accounting framework is then used to explore root sources of the rising inequality. Policy implications are discussed.

The financial intermediation-growth nexus is a widely studied topic in the literature of development economics. Deepening financial intermediation may promote economic growth by mobilizing more investments, and lifting returns to financial resources, which raises productivity. Relying on provincial panel data from China, this paper attempts to examine if regional productivity growth is accounted for by the deepening process of financial development. Towards this end, an appropriate measurement of financial depth is constructed and then included as a determinant of productivity growth. It finds that a significant and positive nexus exists between financial deepening and productivity growth. Given the divergent pattern of financial deepening between coastal and inland provinces, this finding also helps explain the rising regional disparity in China.

This paper proposes a decomposition framework for quantifying contributions of the determinants of poverty to spatial differences or temporal changes in poverty. This framework is then applied to address the issue why poverty incidence is higher in inland than in coastal China. The empirical application requires household or individual income observations which, generally speaking, are not available. Thus, a data-generation method developed by Shorrocks and Wan is introduced to construct such observations from grouped income data. It is found that inland China is poorer than coastal China, mainly due to lower efficiency in resource utilization not to less endowment of resources. Also, trade became poverty-reducing in coastal China in the late 1990s but remained poverty-inducing in inland China. Policy implications are briefly discussed.

The purpose of this paper is to develop two poverty decomposition frameworks and to illustrate their applicability. A given level of poverty is broadly decomposed into an overall inequality component and an overall endowment component in terms of income or consumption determinants or input factors. These components are further decomposed into finer components associated with individual inputs. Also, a change in poverty is decomposed into components attributable to the growth and redistributions of factor inputs. An empirical illustration using Chinese data highlights the importance of factor redistributions in determining poverty levels and poverty changes in rural China.

This paper proposes a framework for incorporating longitudinal distributional changes into poverty decomposition. It is shown that changes in the Sen-Shorrocks-Thon index over time can be decomposed into two components—one component reflects the progressivity of income growth among the original poor, the other measures the extent of downward mobility experienced by the incumbent poor. The decomposition is applied to appraising poverty trends in China between 1988 and 1996. The results indicate that the proposed decomposition can complement the widely-used growth-distribution decomposition in providing insights into poverty dynamics.

PR, IFPRI3; GRP32; Theme 9; Subtheme 9.2; ISI; Country and regional food, nutrition, and agricultural strategies, DSGD

Using a CGE model, PRCGEM, with an updated 2002 I/O table, this paper explores how earnings will be affected in each of 40 separate industries across 31 regions (or 8 regional blocks) of China for the period 2002–07. Labour movement between regions within China is considered. It is found that the direct contribution of WTO membership is small to the whole economy in terms of growth and development. Real GDP will rise only 6.48 per cent (5.6 per cent) in the pure WTO short-run (long-run) shock. Full economic structure change besides WTO shock makes regional output better-off, especially the coastal regions where the economies are well established. Regional labour movement increases by 69.2 per cent in the long-run closure of full economic structural change during the transition period. When regional labour movement is considered, it is found that the Gini coefficient is slightly decreased.

PR, IFPRI3; ISI; GRP32; Theme 9, DSGD

PR, IFPRI3; ISI; GRP32; Theme 9, DSGD

A considerable literature exists on the measurement of income inequality in China and its increasing trend. Much less is known, however, about the driving forces of this trend and their quantitative contributions. Conventional decompositions, by factor components or by population subgroups, only provide limited information on the determinants of income inequality. This paper represents an early attempt to apply the regression-based decomposition framework to the study of inequality accounting in rural China, using household level data. It is found that geography has been the dominant factor but is becoming less important in explaining total inequality. Capital input emerges as a most significant determinant of income inequality. Farming structure is more important than labour and other inputs in contributing to income inequality across households.

China’s recent accession to the WTO is expected to accelerate its integration into the world economy, which aggravates concerns over the impact of globalization on the already rising inter-region income inequality in China. This paper discusses China’s globalization process and estimates an income generating function, incorporating trade and FDI variables. It then applies the newly developed Shapley value decomposition technique to quantify the contributions of globalization, along with other variables, to regional inequality. It is found that (a) globalization constitutes a positive and substantial share to regional inequality and the share rises over time; (b) capital is one of the largest and increasingly important contributor to regional inequality; (c) economic reform characterized by privatization exerts a significant impact on regional inequality; and (d) the relative contributions of education, location, urbanization and dependency ratio to regional inequality have been declining.