The Global Financial Crisis (2007-2008), which began due to the collapse of the U.S. housing market, had a negative effect in many regions across the globe. The global recession which followed the crisis in 2008 and 2009 showed how interdependent and synchronized many of the world's economies had become, with the largest advanced economies showing very similar patterns of negative GDP growth during the crisis. Among the largest emerging economies (commonly referred to as the 'E7'), however, a different pattern emerged, with some countries avoiding a recession altogether. Some commentators have particularly pointed to 2008-2009 as the moment in which China emerged on the world stage as an economic superpower and a key driver of global economic growth. The Great Recession in the developing world While some countries, such as Russia, Mexico, and Turkey, experienced severe recessions due to their connections to the United States and Europe, others such as China, India, and Indonesia managed to record significant economic growth during the period. This can be partly explained by the decoupling from western financial systems which these countries undertook following the Asian financial crises of 1997, making many Asian nations more wary of opening their countries to 'hot money' from other countries. Other likely explanations of this trend are that these countries have large domestic economies which are not entirely reliant on the advanced economies, that their export sectors produce goods which are inelastic (meaning they are still bought during recessions), and that the Chinese economic stimulus worth almost 600 billion U.S. dollars in 2008/2009 increased growth in the region.

As of April 7, 2025, global financial markets are undergoing a sharp correction, primarily triggered by the implementation of extensive tariff policies by the Trump administration. The Dow Jones Industrial Average has fallen 5.5%, with the tech-heavy

Nasdaq Composite officially entering bear market territory after a decline exceeding 20% from recent highs.

The technology sector has been disproportionately affected due to its reliance on global supply chains and international trade exposure. Asian markets have experienced even steeper declines, with the Hang Seng dropping 13.2%, marking its steepest decline since the 1997 Asian financial crisis.

While market sentiment is overwhelmingly negative and volatility remains elevated, our comprehensive analysis suggests this downturn is primarily policy-driven rather than indicative of fundamental economic weaknesses. Drawing comparisons to historical dislocations—most notably the 1987 "Black Monday" crash—today's market environment reveals both significant risk and selective opportunity for long-term investors.

The growing trend of interdependence between the international stock markets indicated the amalgamation of risk across borders that plays a significant role in portfolio diversification by selecting different assets from the financial markets and is also helpful for making extensive economic policy for the economies. By applying different methodologies, this study undertakes the volatility analysis of the emerging and OECD economies and analyzes the co-movement pattern between them. Moreover, with that motive, using the wavelet approach, we provide strong evidence of the short and long-run risk transfer over different time domains from Malaysia to its trading partners. Our findings show that during the Asian financial crisis (1997–98), Malaysia had short- and long-term relationships with China, Germany, Japan, Singapore, the UK, and Indonesia due to both high and low-frequency domains. Meanwhile, after the Global financial crisis (2008–09), it is being observed that Malaysia has long-term and short-term synchronization with emerging (China, India, Indonesia), OECD (Germany, France, USA, UK, Japan, Singapore) stock markets but Pakistan has the low level of co-movement with Malaysian stock market during the global financial crisis (2008–09). Moreover, it is being seen that Malaysia has short-term at both high and low-frequency co-movement with all the emerging and OECD economies except Japan, Singapore, and Indonesia during the COVID-19 period (2020–21). Japan, Singapore, and Indonesia have long-term synchronization relationships with the Malaysian stock market at high and low frequencies during COVID-19. While in a leading-lagging relationship, Malaysia’s stock market risk has both leading and lagging behavior with its trading partners’ stock market risk in the selected period; this behavior changes based on the different trade and investment flow factors. Moreover, DCC-GARCH findings shows that Malaysian market has both short term and long-term synchronization with trading partners except USA. Conspicuously, the integration pattern seems that the cooperation development between stock markets matters rather than the regional proximity in driving the cointegration. The study findings have significant implications for investors, governments, and policymakers around the globe.

The growing trend of interdependence between the international stock markets indicated the amalgamation of risk across borders that plays a significant role in portfolio diversification by selecting different assets from the financial markets and is also helpful for making extensive economic policy for the economies. By applying different methodologies, this study undertakes the volatility analysis of the emerging and OECD economies and analyzes the co-movement pattern between them. Moreover, with that motive, using the wavelet approach, we provide strong evidence of the short and long-run risk transfer over different time domains from Malaysia to its trading partners. Our findings show that during the Asian financial crisis (1997–98), Malaysia had short- and long-term relationships with China, Germany, Japan, Singapore, the UK, and Indonesia due to both high and low-frequency domains. Meanwhile, after the Global financial crisis (2008–09), it is being observed that Malaysia has long-term and short-term synchronization with emerging (China, India, Indonesia), OECD (Germany, France, USA, UK, Japan, Singapore) stock markets but Pakistan has the low level of co-movement with Malaysian stock market during the global financial crisis (2008–09). Moreover, it is being seen that Malaysia has short-term at both high and low-frequency co-movement with all the emerging and OECD economies except Japan, Singapore, and Indonesia during the COVID-19 period (2020–21). Japan, Singapore, and Indonesia have long-term synchronization relationships with the Malaysian stock market at high and low frequencies during COVID-19. While in a leading-lagging relationship, Malaysia’s stock market risk has both leading and lagging behavior with its trading partners’ stock market risk in the selected period; this behavior changes based on the different trade and investment flow factors. Moreover, DCC-GARCH findings shows that Malaysian market has both short term and long-term synchronization with trading partners except USA. Conspicuously, the integration pattern seems that the cooperation development between stock markets matters rather than the regional proximity in driving the cointegration. The study findings have significant implications for investors, governments, and policymakers around the globe.

【リソース】Japan's ODA Annual Report (Summary) 1998 / / Official Development Assistance (ODA): Its Significance and Recent Trends / The 1997 Aid Track Record / ODA and the Asian Currency and Financial Crisis / Health Care (1): Primary Health Care and the Future Shape of Health-Care Assistance / Health Care (2): Efforts to Deal with Specific Diseases and Other Health-Care Challenges / Assistance to Economies in Transition / Regional Conflicts and the Role of ODA / Efforts in Environmental Conservation / Other Global Issues / The Second Tokyo International Conference on African Development / The New Development Strategy / The ODA Charter / Public Understanding / Participatory Development: Assistance for NGO Activities / Efforts to Provide More Efficient and Effective Aid / Terms and Conditions for Yen Loans / General Account Budget for ODA (all government agencies) / ODA Operating Budget (all government agencies) / Major Recipients of Japan's Bilateral Assistance by Aid Scheme (1997) / List of Countries to which Japan is the Top Donor / Japan's Official Development Assistance Charter / History of Japan's Assistance to Developing Countries (1945-1998) / Chart 1: Trends in Major DAC Countries' ODA (Net Disbursement Basis) / Chart 2: Trend of Japan's ODA/GNP Ratio / Chart 3: ODA/GNP Ratios of DAC Member Countries (1997) / Chart 4: Bilateral ODA in the Public Health and Medical Services Sector / Chart 5: Disbursements of Japanese Aid in the Environmental Field / Chart 6: Location of Plaza for International Cooperation / Chart 7: Collaboration between the Ministry of Foreign Affairs and Local Governments / Chart 8: Amount of Money Disbursed Per Person Engaged in ODA / Chart 9: Trends in Procurement Conditions on Japan's ODA Loans / Chart 10: Trends in ODA Loan-Funded Corporate Contracts (By Country, Local Currency Costs Excluded) / Chart 11: Trends in Corporate Japanese Bids Tendered and Won for Projects Worth 1 Billion Yen or More / The Asian Economic Crisis and Assistance to Scholarship Programs / A Health Center for Island Population: The Tamara Health Center Project / Peace Brings Improvements in Water Lifeline / Beyond Survival - The Challenge of Micro-credit (PR Video) / Japanese Aid Can Be a Fountain of Progress: Letter from a Senegalese Village Chief / An Internet Source for ODA-related Information: the MoFA Web Site / A Joint Effort by Japanese and U.S. NGOs and the Japanese Government: Providing Used Bicycles to Teachers in Ghana / The Papua New Guinea Tidal Wave Disaster: Dispatch of a Japan Disaster Relief Team【キーワード】白書_年次報告

Granger causality test for emerging and OECD economy at various frequencies.

Abstract

The main objective of the survey is to determine the prevailing employment, labor-management relations and wage and salary policies and practices in non-agricultural establishments. It aims to provide a benchmark information on employment, labor- management relations and wage and salary practices and policies. Topics covered include establishment profile, employment practices, wage practices, situation of labor management relations and coping mechanisms to globalization.

Geographic coverage

National coverage

Analysis unit

Establishments

Universe

Covered non-agricultural establishments employing 20 or more workers except national postal activities, central banking, public administration and defense and compulsory social security, public education services, public medical, dental and other health services, activities of membership organizations, extra territorial organizations and bodies.

Kind of data

Sample survey data [ssd]

Sampling procedure

Statistical unit: The statistical unit is the establishment. Each unit is classified to an industry that reflects its main economic activity--the activity that contributes the biggest or major portion of the gross income or revenues of the establishment.

Sampling frame: The sampling frame used for the survey was taken from the modified version of the 1996 List of Establishments of the National Statistics Office. This is regularly updated based on the responses to other surveys of the BLES, establishment reports on retrenchments and closures submitted to the Regional Offices of the Department of Labor and Employment and other establishment lists.

Sampling design: Establishments are stratified by 3-digit industry level (except for industries observed to be heterogeneous within their 3-digit level and therefore requires further breakdown at the 4-digit classification). This level of disaggregation was based on industries/sectors covered by the following:
- Industries affected under the General Agreement on Tariffs and Trade(GATT) - Products under the Common Effective Preferential Tariff of the ASEAN Free Trade Agreement (AFTA) - Industries under the Investment Priority Plan of the Board of investment (BOI) - List of export winners of the Department of Trade and Industry (DTI) - Deregulated / liberalized industries - Industries with relatively few players

Establishments in each industry group were classified according to employment size i.e. 20-49, 50-199, and 200 and over. Further if the actual response rate for the survey is at least 80 percent, the sample size for each cell was adjusted to build-in replacement. Geographical location was not considered in the stratification of industries since the policies and practices of establishments do not vary particularly those with regional branches or offices.

Sample size: For IRWS 1999, the sample size was 7,562, of which 5,820 were found to be eligible sampling units.

Note: Refer to Section F of Manual of Instructions

Mode of data collection

Other [oth] mixed method self-accomplished, mailed and face to face

Research instrument

The questionnaire contains the following sections:
Cover page - contains information on purpose of the survey, collection authority, coverage, reference period and due date. It also contains the Establishment Profile that inquires into the main economic activity/principal product, total and female employment, ownership (with foreign equity or wholly Filipino), presence of a union and existence of a collective bargaining agreement in the establishment; Employment Practices - inquires on hiring and retirement and workforce reduction practices; Wage Practices - inquires on the method of fixing or revising wages and salaries, basis of wage payment and grant of allowances, benefits granted to employees and policy in determining days entitlement of sick and vacation leaves; Labor Management Relations - inquires on labor-management communication, union organization and grievance handling; and Coping Mechanisms - inquiries on coping mechanisms to globalization and measures implemented by establishments to cope with economic crisis (1997 Asian financial crisis in the 1999 IRWS questionnaire). Survey Results - selected statistical information from the preceding survey round are provided for information of the respondents.

Cleaning operations

Data are manually and electronically processed. Upon collection of accomplished questionnaires, enumerators perform field editing before leaving the establishments to ensure completeness, consistency and reasonableness of entries in accordance with the field operations manual. The forms are again checked for data consistency and completeness by the field supervisors. The BLES personnel undertake the final review, coding of data based on standard geographical/industrial classification, data entry/encoding and validation and scrutiny of aggregated results. Questionnaires with incomplete or inconsistent entries are returned to the establishments for verification personally or through mail.

Note: Please refer to INDUSTRIAL RELATIONS AT THE WORKPLACE SURVEY (IRWS) 1999 (Manual of Instructions)

Response rate

The response rate was 77.0%

Sampling error estimates

Estimates of the sampling error not computed.