Trade Liberalization and China’s Exports of Renewable Energy Products: Evidence from Product Level Data

This paper studies how firms’ internal organization shapes the impact of international trade. Using establishment-level data from the U.S. Census and a difference-in-difference specification, I find that, relative to standalone firms, conglomerates are more likely to restructure after trade liberalization episodes, focusing on their core competency and improving firm productivity and product market performance. Adjustments through the extensive margin account for the majority of the productivity growth differential between conglomerates and standalones experiencing trade shocks. Aggregate industry productivity remains relatively unchanged in industries dominated by conglomerates’ core business but decreases significantly in others. My findings suggest that firms’ internal organization has important consequences on the effects of trade policies. This paper was accepted by Gustavo Manso, finance.

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The employment and wage effects of export VAT rebates: evidence from China

Review of World Economics ◽

10.1007/s10290-020-00400-3 ◽

2020 ◽

Author(s):

Bo Gao ◽

Jing Ma ◽

Zheng Wang

Keyword(s):

Employment Effect ◽

High Productivity ◽

Product Level ◽

Level Data ◽

Wage Effects ◽

Reallocation Of Resources

AbstractThis paper studies the employment and wage effects of VAT rebates to exporters with comprehensive firm-product-level data of China. It is found that the adjustments in VAT rebates significantly and positively affect firm’s employment but have no statistically significant effect on firm’s wage. Moreover, this paper finds that the employment effect of VAT rebates is heterogeneous across firms. In particular, low-productivity firms are more sensitive to the adjustments of VAT rebates than high-productivity firms, suggesting that an increase of VAT rebates may cause mis-reallocation of resources.

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The Role of Trade Liberalization in Carbon Dioxide Emission: Evidence From Heterogeneous Panel Estimations

International Journal of Financial Research ◽

10.5430/ijfr.v10n5p228 ◽

2019 ◽

Vol 10 (5) ◽

pp. 228

Author(s):

Gholamreza Zandi ◽

Muhammad Haseeb

Keyword(s):

Carbon Dioxide ◽

Developing Countries ◽

Renewable Energy ◽

Trade Liberalization ◽

Causal Relationship ◽

Environmental Degradation ◽

Carbon Dioxide Emission ◽

Energy Utilization ◽

Long Run ◽

Heterogeneous Panel

In the present globalized world, production forms are progressively divided across nations. Consequently, domestic consumption in one nation is progressively fulfilled by worldwide supply chains. This spectacle has pulled policy and widespread intellectual discussions on the assignment of greenhouse gas (GHG) emanations, especially carbon dioxide (CO2) emission; these are accountabilities connected to global trade since worldwide trade causes net carbon dioxide emission. The aim of the present study is to examine the impact of trade liberalization on carbon dioxide emission. We used the panel data of 105 developed and developing countries from 1990 to 2017. The results of FMOLS and DOLS confirm that all variables are connected in the long-run period. The results of long run coefficient confirm that that the trade liberalization has a positive effect on environmental degradation and cause to increase environmental degradation. Likewise, economic growth and energy consumption has also a positive and significant impact on environmental degradation. However, we find an evidence of negative and significant impact of renewable energy utilization on environmental degradation. Finally, the results of heterogeneous panel causality confirm that there is a uni-directional causal relationship between trade liberalization and environmental degradation where causality is running from trade liberalization to environmental degradation. However, we find a bi-directional causal relationship of environmental degradation with energy utilization and renewable energy utilization in all selected developed and developing countries.

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Product-level profitability

Journal of Enterprise Information Management ◽

10.1108/jeim-05-2019-0127 ◽

2019 ◽

Vol 33 (1) ◽

pp. 214-237

Author(s):

Hannu Hannila ◽

Joni Koskinen ◽

Janne Harkonen ◽

Harri Haapasalo

Keyword(s):

Business Processes ◽

Data Driven ◽

Product Portfolio ◽

Data Governance ◽

Content Type ◽

Technical Product ◽

Product Level ◽

Level Data ◽

Corporate Level

Purpose The purpose of this paper is to analyse current challenges and to articulate the preconditions for data-driven, fact-based product portfolio management (PPM) based on commercial and technical product structures, critical business processes, corporate business IT and company data assets. Here, data assets were classified from a PPM perspective in terms of (product/customer/supplier) master data, transaction data and Internet of Things data. The study also addresses the supporting role of corporate-level data governance. Design/methodology/approach The study combines a literature review and qualitative analysis of empirical data collected from eight international companies of varying size. Findings Companies’ current inability to analyse products effectively based on existing data is surprising. The present findings identify a number of preconditions for data-driven, fact-based PPM, including mutual understanding of company products (to establish a consistent commercial and technical product structure), product classification as strategic, supportive or non-strategic (to link commercial and technical product structures with product strategy) and a holistic, corporate-level data model for adjusting the company’s business IT (to support product portfolio visualisation). Practical implications The findings provide a logical and empirical basis for fact-based, product-level analysis of product profitability and analysis of the product portfolio over the product life cycle, supporting a data-driven approach to the optimisation of commercial and technical product structure, business IT systems and company product strategy. As a virtual representation of reality, the company data model facilitates product visualisation. The findings are of great practical value, as they demonstrate the significance of corporate-level data assets, data governance and business-critical data for managing a company’s products and portfolio. Originality/value The study contributes to the existing literature by specifying the preconditions for data-driven, fact-based PPM as a basis for product-level analysis and decision making, emphasising the role of company data assets and clarifying the links between business processes, information systems and data assets for PPM.

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