Methods for Ex Post Economic Evaluation of Free Trade Agreements

Evaluating the economic impact of an FTA is an important part of the monitoring and surveying process that should follow the establishment of an FTA. This paper presents methods for evaluating the trade and welfare effects of an FTA. These methods show how to (i) compute indicators for the utilization and value of preferences, (ii) qualitatively assess trade creation and diversion, (iii) quantitatively analyze the FTA‘s trade effects with trade indicators and the gravity model, and (iv) make inferences about economic welfare. This paper specifies the formulas, computational techniques, and data used for each evaluation method, and describes how to interpret the output from each method with examples taken from countries such as Viet Nam, Indonesia, and Cambodia. The strengths and limitations of each method are also discussed.regionalization; evaluation methods; preferential tariffs; trade indicators; gravity model; free trade agreements; Asia

FDI Effects of ASEAN Integration

For the past two decades, ASEAN Member States have pursued intra-regional market liberalization in order to provide more flexibility to multinationals and therefore promote the region as a competitive production platform. Attracting FDI has been a key objective of this regional project. This paper describes and analyzes recent trends in FDI to and among ASEAN countries, mainly comparing FDI patterns before and after the Asian Crisis, to characterize and assess the region‟s strategies to liberalize and facilitate investment. We find that FDI flows to ASEAN countries suffered after the Asian Crisis but have picked up since 2005. Moreover, ASEAN FDI is dominated by Singapore. In addition, the sectoral distribution of FDI has changed in some members of ASEAN (i.e., Malaysia, Singapore, and Thailand) but not in others. We also perform an econometric analysis of the determinants of FDI to check for ASEAN-specific changes in FDI in the post-Crisis period. Our results, after controlling for a host of factors, indicate that ASEAN countries suffered a fall in total FDI but experienced an increase in intra-regional FDI after 1998. Moreover, we do not find any significant impact of FDI in China on ASEAN FDI.Association of South-east Asian Nations (ASEAN); Foreign Direct Investment (FDI); Economic Integration; Knowledge Capital Model

FDI EFFECTS OF ASEAN INTEGRATION

For the past two decades, ASEAN Member States have pursued intra-regional market liberalization in order to provide more flexibility to multinationals and therefore promote the region as a competitive production platform. Attracting FDI has been a key objective of this regional project. This paper describes and analyzes recent trends in FDI to and among ASEAN countries, mainly comparing FDI patterns before and after the Asian Crisis, to characterize and assess the region?s strategies to liberalize and facilitate investment. We find that FDI flows to ASEAN countries suffered after the Asian Crisis but have picked up since 2005. Moreover, ASEAN FDI is dominated by Singapore. In addition, the sectoral distribution of FDI has changed in some members of ASEAN (i.e., Malaysia, Singapore, and Thailand) but not in others. We also perform an econometric analysis of the determinants of FDI to check for ASEAN-specific changes in FDI in the post-Crisis period. Our results, after controlling for a host of factors, indicate that ASEAN countries suffered a fall in total FDI but experienced an increase in intra-regional FDI after 1998. Moreover, we do not find any significant impact of FDI in China on ASEAN FDI.ASSOCIATION OF SOUTH EAST ASIAN NATIONS (ASEAN), FOREIGN DIRECT INVESTMENT (FDI), ECONOMIC INTEGRATION, ASEAN INVESTMENT AREA, KNOWLEDGE CAPITAL MODEL

Covering many points with a small-area box

Let $P$ be a set of $n$ points in the plane. We show how to find, for a given integer $k>0$, the smallest-area axis-parallel rectangle that covers $k$ points of $P$ in $O(nk^2 \log n+ n\log^2 n)$ time. We also consider the problem of, given a value $\alpha>0$, covering as many points of $P$ as possible with an axis-parallel rectangle of area at most $\alpha$. For this problem we give a probabilistic $(1-\varepsilon)$-approximation that works in near-linear time: In $O((n/\varepsilon^4)\log^3 n \log (1/\varepsilon))$ time we find an axis-parallel rectangle of area at most $\alpha$ that, with high probability, covers at least $(1-\varepsilon)\mathrm{\kappa^*}$ points, where $\mathrm{\kappa^*}$ is the maximum possible number of points that could be covered

The Invisible Risk: The Data-sharing Activities of Data Brokers and Information Leakage

Data brokers are the major players in the market for collecting, selling and sharing user information. This paper considers data brokers’ data sharing activities as a co-opetition between data brokers and investigates how the information collecting and sharing activities may lead to information leakage on the dark web. We find that S&P 1,500 firms experience higher information leakage when sharing more customer information with data brokers through third-party cookies. Further, using all the registered data brokers and their competitors as the sample, we observe that registered data brokers are more susceptible to information leakage with data sharing activities than unregistered data brokers. Our study provides initial evidence on the consequences of data brokers’ data sharing activities

What Do You Know about Alternative Energy? Development and Use of a Diagnostic Instrument for Upper Secondary School Science

The need for renewable and non-fossil fuels is now recognised by nations throughout the world. Consequently, an understanding of alternative energy is needed both in schools and in everyday life-long learning situations. This study developed a two-tier instrument to diagnose students’ understanding and alternative conceptions about alternative energy in terms of: sources of alternative energy, greenhouse gas emission, as well as advantages, and disadvantages. Results obtained with Years 10 and 11 students (n = 491) using the 12-item two-tier instrument (α = 0.61) showed that students’ understanding of alternative energy was low (M = 7.03; SD = 3.90).The 23 alternative conceptions about alternative energy sources that could be identified from the instrument are reported. The implications for teaching and learning about alternative energy and suggestions for further development and improvement of the instrument are presented