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There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments in nonparametric econometrics. Therefore, we choose to limit our focus on the following areas. In Section 2, we review the recent developments of nonparametric estimation and testing of regression functions with mixed discrete and continuous covariates. We discuss nonparametric estimation and testing of econometric models for nonstationary data in Section 3. Section 4 is devoted to surveying the literature of nonparametric instrumental variable (IV) models. We review nonparametric estimation of quantile regression models in Section 5. In Sections 2–5, we also point out some open research problems, which might be useful for graduate students to review the important research papers in this field and to search for their own research interests, particularly dissertation topics for doctoral students. Finally, in Section 6 we highlight some important research areas that are not covered in this paper due to space limitation. We plan to write a separate survey paper to discuss some of the omitted topics.

In this chapter, we consider the nonparametric estimation of the average treatment effect (ATE) based on direct estimation of the conditional treatment effect. We establish the asymptotic distribution of the proposed ATE estimator. We also consider consistent testing for a parametric functional form for the conditional treatment effect function. A small-scale Monte Carlo simulation study is reported to examine the finite sample performance of the proposed estimator.

Applying a computable general equilibrium model to assess the impact of tariffs between the US and China, Taiwan stands to gain from trade diversion of the trade war between the two largest world economies in the short term.

Initially, Taiwan suffered a minor loss from the sector-specific tariff on steel and aluminum imposed by the US. However, its loss is mitigated after counting counter measures from foreign countries. The cumulated US tariffs and China's retaliations led to trade diversion effect. Taiwan's initial loss from the steel and aluminum tariffs was over compensated by a series of trade war between the US and China.

Under the scenario of the cumulated tariffs of $250 billion of US imports and China's retaliations of $110 billion on US goods, the social welfare, exports, import and trade balance in Taiwan increased. Its terms of trade improved as well. Real wage increases slightly more for unskilled labor than for skilled labor. The short-term effect of the trade war has positive effect on all macro indicators of Taiwan's economy.

On sectoral shift, Taiwan's export will gain the most in precision engineering products ($2,941.6 million), followed by electronics ($310.7 million) and agricultural products ($31.3 million). The negative effects are in sectors such as business services ($58.323 million), other services ($46.9 million), transportation service ($36.6 million), trade service ($25.3 million), and finance service ($24.5 million). Taiwan's total imports will increase by 0.59%, whereas its total export will increase by 0.33%. However, total trade balance still increases by $451.1 million.

The study also finds that Taiwan has a high degree of overlapping export commodities with China in the US market, much higher than most major trading partners for the US, yet its market share for those products in the US is ranged from 1% to 5% only. Moreover, more than 60% of Taiwan's export to the US is in intermediate goods which have less product differentiation than those in final consumption goods. These two factors will provide an opportunity for Taiwan to exploit the US market.

Though the short-term effect of trade war is positive, Taiwan needs to have a long-range planning amid the external shocks. Policy implications for Taiwan are to map out a cosmopolitan view of its geo-strategy by diversifying outward foreign direct investment and trade destinations. It needs to reduce the “systemic risk” of relying on single market in China which is vulnerable to the uncertainty in the US–China relations. If the trade war lasts too long, Taiwan would need to reevaluate its triangular trade-investment nexus with China and the US as well as its role in the global supply chain.

Data has become one of the most significant instruments in e-commerce innovation. Benefits to the entire society can be summarized as following: from the government’s perspective - to assess the impact of e-commerce to the economy; for merchants - to understand consumers’ needs; and for consumers - to be offered with the right product he/she is looking for. The digital revolution in the past five years has shown the need to offer more differentiated services than the physical stores, when consumers are not able to try and touch products. It is for this reason that e-commerce has continuously developed and transformed Research Online, Purchase Offline into a true experience. Considering the future of e-commerce is to enhance economic development and growth, this research will discuss the disruption of Research and Development through big data. The core objective of this research is to propose a predictive model to deeply understand consumer behavior by analyzing new regulations and transaction records.

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. Besides, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management, and so on. In recent years, knowledge graph techniques in China are also developing rapidly and different Chinese knowledge graphs have been built to support various applications. Under the background of “One Belt One Road (OBOR)” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China on developing knowledge graph is also a good reference. Thus, in this chapter, the authors mainly introduce the development of Chinese knowledge graphs and their applications. The authors first describe the background of OBOR, and then introduce the concept of knowledge graph and three typical Chinese knowledge graphs, including Zhishi.me, CN-DBpedia, and XLORE. Finally, the authors demonstrate several applications of Chinese knowledge graphs.

Since the beginning of the new millennium, Confucian doctrines on one’s self-cultivation have been re-introduced to curriculum in China. The revived cherish of the Confucian legacy in the twenty-first century is a reverse from the official rejection of Confucianism in the Mao era (1950–1976). It also appears as a counterweight to the individualism proliferating among the Chinese youths born at the beginning of the new millennium (Gen Z). The re-introduction of Confucianism is thus ideologically purposeful. Yet how does the mixed exposure to Confucius’ legacy and the modern idea of self-awareness impact this cohort of young people, in particular their way of learning? This chapter focusses on Chinese Gen Z studying in Australia. Using the Bourdieuan theory of human habitus, this chapter examines how these students negotiate between the ideas of self-cultivation and self-awareness, and what implications such experiences have in an intercultural academic community.