Manufacturing Innovation

(ProQuest: ... denotes non-USASCII text omitted.) The annual Global Innovation Index released in September 2021 ranked China twelfth, surpassing developed economies such as Japan, Israel, and Canada and raising fears in the United States amidst sluggish growth in North America and strong growth in the Asia Pacific region.1 Interestingly, the United States government responded by boycotting the Beijing Olympic Games, citing human rights abuses as the main reason.2 A tech war between China and the United States brewed beneath the diplomatic rancor over the attendance at the Olympic Games. Part I documents how the United States has assisted China's tech and intellectual property domination through President Nixon's historic visit to China, giving China Most Favorite Nation (MFN) status and ascending China to the World Trade Organization (WTO). [...]under Deng Xiaoping's leadership during the reform period, China rapidly developed its special economic zones (SEZs), laying the foundation for subsequent tech innovation and production. [...]broadcasting, telecommunications, office machines, computers, integrated circuits, and cell phones are among China's notable exports to the world.9 China dominates in commodities and raw materials, exporting refined petroleum, cotton, plywood, and tea.10 For agricultural products, China occupies the perch as the world's largest producer. Shenzhen rose as the largest among the four.18 Shenzhen, a small fishing locale in the southern part of China's southern province, Guangdong, served as the pioneer of Deng Xiaoping's embrace of economic reforms.19 A market-oriented economy took root in Shenzhen, allowing foreign companies and entities from Hong Kong and Macau to operate and allowing Chinese talents the freedom to leave their hometowns and move into the SEZs.20 Cheap labor proved to be another significant factor facilitating China's rise as a global manufacturer.21 In the 1980s, multinational corporations from Taiwan, Japan, and South Korea, as well as domestic Chinese companies, opened their factories in the SEZs and other cities in China to take advantage of the cheap and plentiful labor force.22 Indeed, when Deng Xiaoping began his pilot SEZs, China's young workers who wished to lift themselves out of poverty descended into the economic zones in search of better opportunities.23 Shenzhen grew from a population of 59,000 in 1980 to a population of 12,357,000 in 2020.24 The new migrants became the workers, participants, and stakeholders in the global manufacturing frontier.25 Because of the abundance of cheap labor, manufacturers in China have no difficulty keeping production prices low and pleasing consumers and businesses worldwide.26 China's currency manipulation is another factor propelling China to its domination in global manufacturing.27 The United States Congress attempted numerous times to introduce legislation to combat China's currency manipulation.28 China artificially devalued its currency through government control of the exchange rate and refused to let the Chinese Renminbi (RMB) float.29 Despite strong criticisms from the United States, China refuses to allow its currency to freely float.30 China's currency manipulations, according to critics, caused the widening of trade deficits between the United States and China.31 China's currency manipulation allows products to be manufactured at lower prices, hampering competitors and thereafter replacing them.32 In order to cope with China's currency practices, United States manufacturers facing their own existential crises must decide to either outsource jobs overseas or face large risks, including financial ruin.33 The United States lost millions of manufacturing jobs due to massive job outsourcing as the trade deficits between the United States and China continued to persist.34 Geopolitically, in shaping post-Cold-War powers, the United States decided to assist China in its transformation from a poverty-stricken country to a global manufacturer.

The stock market and NO2 emissions effects of COVID‐19 around the world

In this paper, we study the impact of the coronavirus disease 2019 pandemic in estimated panel vector autoregression models for 92 countries. The large cross‐section of countries allows us to shed light on the heterogeneity of the responses of stock markets and nitrogen dioxide emissions as high‐frequency measures of economic activity. We quantify the effect of the number of infections and four dimensions of policy measures: (1) containment and closure, (2) movement restrictions, (3) economic support, and (4) adjustments of health systems. Our main findings show that a surprise increase in the number of infections triggers a drop in our two measures of economic activity. Propping up economic support measures, in contrast, raises stock returns and emissions and, thus, contributes to the economic recovery. We also document vast differences in the responses across subsets of countries and between the first and the second wave of infections.

Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19

Dealing with structural breaks is an essential step in most empirical economic research. This is particularly true in panel data comprised of many cross-sectional units, which are all affected by major events. The COVID-19 pandemic has affected most sectors of the global economy;however, its impact on stock markets is still unclear. Most markets seem to have recovered while the pandemic is ongoing, suggesting that the relationship between stock returns and COVID-19 has been subject to structural break. It is therefore important to know if a structural break has occurred and, if it has, to infer the date of the break. Motivated by this last observation, the present article develops a new break detection toolbox that is applicable to different sized panels, easy to implement and robust to general forms of unobserved heterogeneity. The toolbox, which is the first of its kind, includes a structural change test, a break date estimator, and a break date confidence interval. Application to a panel covering 61 countries from January 3 to September 25, 2020, leads to the detection of a structural break that is dated to the first week of April. The effect of COVID-19 is negative before the break and zero thereafter, implying that while markets did react, the reaction was short-lived. A possible explanation is the quantitative easing programs announced by central banks all over the world in the second half of March.

Does the Shield Effect of CSR Work in Crises? Evidence in Korea

This paper investigates the impact of corporate social responsibility (CSR) on shareholders' wealth during market downturn, focusing on the market crash caused by the COVID-19 pandemic and its aftermaths. We evaluate the relationship between firms' CSR and stock returns using a sample of 803 firms listed on the Korean stock market. The results of our study reveal that firms' pre-crisis CSR activities do not protect shareholders' wealth during the crisis;in fact, they negatively affected stock returns during the COVID-19 crisis. This finding is consistent across several robustness tests and challenges the prevailing notion that CSR is solely a philanthropic endeavor. This study suggests that firms need to reconsider their CSR approach in order to better align it with shareholders' interest.

BIST Tourism and BIST Electricity Index Relationship

In this study, which is based on daily data, the relationship between BIST electricity index and BIST tourism index was measured between 2012:M9 – 2022:M9 periods. The aim of the study is to measure the relationship between BIST electricity index and BIST tourism index. VAR Granger causality test was applied to determine whether there is any causal relationship between the variables. It has been determined as a result of the analysis that the BIST electricity index has no effect on the BIST tourism index. Two-way ineffectiveness was determined among the variables. In addition, it was obtained as a result of the analysis that the applied correlation relationship was weak between these variables. The results obtained from the study are important in terms of measuring the effects among BIST indices.

The Moderating Effects of Corporate Social Responsibility on Corporate Financial Performance: Evidence from OECD Countries

This study aims to investigate the nature and intensity of the changes in corporate financial performance due to the corporate social responsibility (CSR) disclosures as a result of certain relationships between corporate governance and company performance in the non-financial sector. This study selected 625 non-financial companies across six organizations for economic cooperations (OECD) countries' stock markets for the period of 10 years (2012–2021). For this qualitative study, corporate governance, financial performance, and corporate social responsibility score data were collected from the DataStream, a reliable database for examining the research on OECD countries' listed companies. For the data analysis we applied various statistical tools such as regression analysis and moderation analysis. The findings of the study show that all attributes of the corporate governance mechanism, except for audit board attendance, have significant positive impacts on financial performance indicators for all the selected OECD economies except the country France. France's code of corporate governance has a significant negative impact on return on asset (ROA) and return on equity (ROE) due to differences in cultural and operational norms of the country. The audit board attendance has no significant impact on ROA. Moreover, all the attributes except board size (BSIZ) have significant positive impacts on the earnings per share (EPS) in Spain, The United Kingdom (UK) and Belgium. The values obtained from the moderation effect show that Corporate social responsibility is the key factor in motivating corporate governance practices which eventually improves corporate financial performance. However, this study advocated the implications, Investors and stakeholders should consider both corporate governance and CSR disclosures when making investment decisions. Companies that prioritize both governance and CSR tend to have better financial performance and are more likely to mitigate risks. Moreover, the policy makers can improve the code of corporate governance in order to attain sustainable development in the stock market.

EMPLOYING ARTIFICIAL NEURAL NETWORKS AND MULTIPLE DISCRIMINANT ANALYSIS TO EVALUATE THE IMPACT OF THE COVID-19 PANDEMIC ON THE FINANCIAL STATUS OF JORDANIAN COMPANIES

Aim/Purpose This paper aims to empirically quantify the financial distress caused by the COVID-19 pandemic on companies listed on Amman Stock Exchange (ASE). The paper also aims to identify the most important predictors of financial distress pre- and mid-pandemic. Background The COVID-19 pandemic has had a huge toll, not only on human lives but also on many businesses. This provided the impetus to assess the impact of the pandemic on the financial status of Jordanian companies. Methodology The initial sample comprised 165 companies, which was cleansed and reduced to 84 companies as per data availability. Financial data pertaining to the 84 companies were collected over a two-year period, 2019 and 2020, to empirically quantify the impact of the pandemic on companies in the dataset. Two approaches were employed. The first approach involved using Multiple Discriminant Analysis (MDA) based on Altman's (1968) model to obtain the Z-score of each company over the investigation period. The second approach involved developing models using Artificial Neural Networks (ANNs) with 15 standard financial ratios to find out the most important variables in predicting financial distress and create an accurate Financial Distress Prediction (FDP) model. Contribution This research contributes by providing a better understanding of how financial distress predictors perform during dynamic and risky times. The research confirmed that in spite of the negative impact of COVID-19 on the financial health of companies, the main predictors of financial distress remained relatively steadfast. This indicates that standard financial distress predictors can be regarded as being impervious to extraneous financial and/or health calamities. Findings Results using MDA indicated that more than 63% of companies in the dataset have a lower Z-score in 2020 when compared to 2019. There was also an 8% increase in distressed companies in 2020, and around 6% of companies came to be no longer healthy. As for the models built using ANNs, results show that the most important variable in predicting financial distress is the Return on Capital. The predictive accuracy for the 2019 and 2020 models measured using the area under the Receiver Operating Characteristic (ROC) graph was 87.5% and 97.6%, respectively. Recommendations Decision makers and top management are encouraged to focus on the identified for Practitioners highly liquid ratios to make thoughtful decisions and initiate preemptive actions to avoid organizational failure. Recommendations This research can be considered a stepping stone to investigating the impact of for Researchers COVID-19 on the financial status of companies. Researchers are recommended to replicate the methods used in this research across various business sectors to understand the financial dynamics of companies during uncertain times. Impact on Society Stakeholders in Jordanian-listed companies should concentrate on the list of most important predictors of financial distress as presented in this study. Future Research Future research may focus on expanding the scope of this study by including other geographical locations to check for the generalisability of the results. Future research may also include post-COVID-19 data to check for changes in results. © 2023 Informing Science Institute. All rights reserved.

The Bank of Japan's exchange traded fund purchases: a help or hindrance to market efficiency?

We examine the impact of the Bank of Japan's exchange traded fund (ETF) purchases on two aspects of market efficiency—long-range dependence and price delay—of the TOPIX and Nikkei 225 indices. An increase in ETF purchases results in lower long-range dependence for both indices while the impact on the price delay varies according to index and measure. A sub-period analysis shows that the impact on market efficiency varies over time, with the dominant pattern being a delayed harmful effect, followed by a positive impact and thereafter a negative effect. The implications of these findings are discussed.

Asian perspective of capital market performance amid the COVID 19 pandemic

PurposeThe purpose of this research is to investigate the short-term capital markets' reactions to the public announcement first local detection of novel corona virus (COVID 19) cases in 12 major Asian capital markets.Design/methodology/approachUsing the constant mean return model and the market model, an event study methodology has been implied to determine the cumulative abnormal returns (CARs) of 10 pre and post-event trading days. The statistical significance of the data was assessed using both parametric and nonparametric test statistics.FindingsFirst discovery of local COVID 19 cases had a substantial impact on all 12 Asian markets on the event day, as shown by statistically significant negative average abnormal return (AAR) and cumulative average abnormal return (CAAR). The single factor ANOVA result has also demonstrated that there is no variability among 12 regional markets in terms of short-term market responses. Furthermore, there is little evidence that these major Asian stock market indices differ significantly from the FTSE All-World Index which might suggest possible spillover impact and co-integration among the major Asian capital markets. The study further discovers that market capitalization and liquidity did not have any significant impact on market reaction to announcement.Research limitations/implicationsThe study's contribution might have been compromised by the absence of socio-demographic, technical, financial and other significant policy factors from the analysis.Practical implicationsThese findings will be considerably helpful in tackling this unprecedented epidemic issue for personal and institutional investors, industrial and economic experts, government and policymakers in assessing the market in special circumstances, diversifying risk and developing financial and monetary policy proposals.Originality/valueThis paper is the first to examine the effects of local COVID 19 detection announcement on major Asian capital markets. This study will add to the literature by investigating unusual market returns generated by infectious illness outbreaks and the overall market efficiency and investors' behavioral pattern of major Asian capital markets.

Hedging potentials of green investments against climate and oil market risks

PurposeThis study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.Design/methodology/approachThe study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan's (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West's model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.FindingsThe study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.Originality/valueThe study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.

Islamic Bank Merger and Economic Crisis: Event Study Analysis: Acces la Success

This event study examines the stock price reaction to the merger announcement of three major Islamic banks in Indonesia, namely BNIS, BRIS, and BSM to become Indonesia Islamic Bank (ticker code BRIS). This study analyzes whether there is an abnormal return around the merger announcement on 14 days window period. Using a daily stock price of BRIS, market index, and trading volume we calculated abnormal return and risk using market model Sharpe 's single index model. Analysis of the 14 days window period found that there is an insignificant abnormal return before and after the Islamic banking merger and Indonesia Stock Exchange has been categorized as weak-form efficiency. The results of statistical tests reveal that stock returns and trading volume react positively after the merger announcement and are significant at 5% alpha.

NON-FINANCIAL REPORTING OF TOP COMPANIES IN TURBULENT ENVIRONMENT

Nowadays, the non-financial reporting of companies shows more and more interest both among companies and investors, who are no longer interested only in the reported figures. However, the pandemic period also left its mark among large companies. Our research concerns the global top 50 companies and the non-financial reports published by them before, during and after the pandemic generated by the novel coronavirus. The purpose of our paper is to illustrate how these entities present the story and the CSR actions taken during a time when most companies struggled to survive. To achieve these objectives, we used qualitative and quantitative research. Namely, we analyzed the entities' non-financial reports, to identify their social responsibility actions and we used the NVivo program in order to highlight which are the most representative words used in non-financial reporting in the three analyzed moments, namely before, during and after the COVID-19 pandemic The results of the study reflect that in a turbulent environment, companies tend to present less complex reports and use more ambiguous tone. Also, our research highlights the fact that CSR activities undertaken ware greatly reduced during the pandemic period.

Sánchez Arévalo, J. L., Moreira de Sousa, G., & Malta Meurer, R. (2022). Causal effect between the Ibovespa stock market and Shanghai, S&P500, Merval and Nikkei indicators. Cuadernos de Economía

This paper analyzes the causal relationship between the Brazilian stock market indicator and other stock exchange indicators. Specifically, the study time incorporates the world crisis caused by the covid-19 and the war over the price of oil. Were used the differentiated series considering the existence of a unit root, the VAR and Granger Causality models were subsequently estimated. The results show that the causality between the Ibovespa with the S&P500 and Nikkei is bidirectional. These results are consistent when relating the degree of commercial exchange and the origin of foreign investment in Brazil. © 2023, Cuadernos de Economia (Colombia). All Rights Reserved.

Optimization of investment performance based on personality traits: Acces la Success

To achieve their investment objectives, each investor has a strategy in place. A high amount of personality traits element influenced (perceived) investment performance. The purpose of this research was to test how the Big Five personality qualities affected (perceived) investment performance. The hypotheses were tested using PLS-SEM. Individual stock investors in Indonesia were studied, and the results revealed that openness and neuroticism personality had a negative impact on (perceived) investment performance. Consciousness, extraversion, and agreeableness, on the other hand, all had a positive effect on (perceived) investment performance. This research shows the importance of personality traits when allocating assets to meet investment objectives and improves behavioral finance theory.

Environmental reporting by Indonesian agricultural companies around the spread of the COVID-19 epidemic

The purpose of this article is to see if there was a change in the amount of environmental reporting by agricultural firms after the COVID-19 epidemic spread in Indonesia. This study also examines the difference in the degree of environmental reporting between companies that publish sustainability reporting and those that do not in the period pre- and post-COVID-19. In addition, determinant factors for the extent of environmental reporting are also explored. This study utilizes 23 companies as a sample, i.e., the Indonesia Stock Exchange-listed agricultural enterprises in 2019 and 2020. The paired sample t-test results show that environmental reporting rose following the spread of the COVID-19 pandemic compared to reporting levels before the pandemic. In addition, the environmental reporting of companies that publish sustainability reporting is significantly higher than that of those that do not. This finding implies that despite the hard time facing COVID-19, the companies keep maintaining incentives to care more about the environment, which is marked by increased environmental reporting. Meanwhile, the factor that affects the amount of environmental exposure is the firm's size. Hence, a company's level of environmental reporting will increase as its assets grow in size.

The impact of COVID-19 on the portfolio optimization

PurposeThis article unveils first the lead–lag structure between the confirmed cases of COVID-19 and financial markets, including the stock (DJI), cryptocurrency (Bitcoin) and commodities (crude oil, gold, copper and brent oil) compared to the financial stress index. Second, this paper assesses the role of Bitcoin as a hedge or diversifier by determining the efficient frontier with and without including Bitcoin before and during the COVID-19 pandemic.Design/methodology/approachThe authors examine the lead–lag relationship between COVID-19 and financial market returns compared to the financial stress index and between all markets returns using the thermal optimal path model. Moreover, the authors estimate the efficient frontier of the portfolio with and without Bitcoin using the Bayesian approach.FindingsEmploying thermal optimal path model, the authors find that COVID-19 confirmed cases are leading returns prices of DJI, Bitcoin and crude oil, gold, copper and brent oil. Moreover, the authors find a strong lead–lag relationship between all financial market returns. By relying on the Bayesian approach, findings show when Bitcoin was included in the portfolio optimization before or during COVID-19 period;the Bayesian efficient frontier shifts to the left giving the investor a better risk return trade-off. Consequently, Bitcoin serves as a safe haven asset for the two sub-periods: pre-COVID-19 period and COVID-19 period.Practical implicationsBased on the above research conclusions, investors can use the number of COVID-19 confirmed cases to predict financial market dynamics. Similarly, the work is helpful for decision-makers who search for portfolio diversification opportunities, especially during health crisis. In addition, the results support the fact that Bitcoin is a safe haven asset that should be combined with commodities and stocks for better performance in portfolio optimization and hedging before and during COVID-19 periods.Originality/valueThis research thus adds value to the existing literature along four directions. First, the novelty of this study lies in the analysis of several financial markets (stock, cryptocurrencies and commodities)' response to different pandemics and epidemics events, financial crises and natural disasters (Correia et al., 2020;Ma et al., 2020). Second, to the best of the authors' knowledge, this is the first study that examine the lead–lag relationship between COVID-19 and financial markets compared to financial stress index by employing the Thermal Optimal Path method. Third, it is a first endeavor to analyze the lead–lag interplay between the financial markets within a thermal optimal path method that can provide useful insights for the spillover effect studies in all countries and regions around the world. To check the robustness of our findings, the authors have employed financial stress index compared to COVID-19 confirmed cases. Fourth, this study tests whether Bitcoin is a hedge or diversifier given this current pandemic situation using the Bayesian approach.

Performance Evaluation of Tourism and Hospitality Companies in the Indian Stock Market, A Post-Covid-19 perspective

The Covid-19 pandemic affected the tourism industry's supply chain and reflected its performance and financial market. This paper aims to evaluate the performance of selected tourism-related companies listed in the Indian stock market. This study evaluates the performance of companies share prices and their business performance in post covid perspective. No studies have been conducted before on the performance evaluation of tourism-related companies listed in the Indian Stock Market from a post covid perspective. Fundamental data analysis for the reports from 2018 to 2022 and the share price charts from 2019 to 2022 was undertaken by twenty-five companies in four categorised sectors: Travel Agencies, hotels and resorts, Airlines, and Amusement parks. This study unveils that companies are underperforming in post covid and at the same time, they performed well in the share market after a negative correction due to covid-19. Airline companies are the most affected and least performed in the stock market by their share price growth. The study result helps investors and people interested in the share market assess the influence of a pandemic situation and to help in decision-making related to investment in the tourism and hospitality industry.

COVID-19 full vaccination and blockchain size: empirical evidence from the cryptocurrency market

PurposeThis paper aims to analyse COVID-19 indices and blockchain features on Bitcoin and Ethereum returns, respectively. The authors focus on the most used and owned cryptocurrencies that cover Europe, the US and Asian countries.Design/methodology/approachAn autoregressive distributed lag panel (pooled mean group and mean group) is utilized, and a robustness check is incorporated by using a Random Effect Model and Generalized Method of Moments (GMM).FindingsFour new findings were discovered, including (1) the vaccine confidence index (VCI) pushes economic recovery and increased demand for the Bitcoin market, but the opposite result was interestingly observed from Ethereum;(2) the blockchain features were revealed to be essential to Bitcoin, while they were irrelevant to Ethereum for short-run country-specific results;(3) the hash rate and network difficulty moved inversely during the pandemic;and (4) the government played a significant role in taking action during uncertain times and regarding cryptocurrency policies.Research limitations/implicationsVCI is constructed by the most used vaccine type in our sample countries (i.e. Pfizer), as the data for a specific classification by each type is still unavailable.Practical implicationsProviding an evenly distributed vaccination program primary vaccination series against COVID-19 to the citizens is an essential duty of the government. Bitcoin policymakers and investors should watch the COVID-19 vaccine distributions closely as it will affect its return. Ethereum is emphasized to keep developing its smart contract which appeared to outplay other blockchain features. Cryptocurrency investors should be wise in their investment decisions by analysing the news thoroughly.Social implicationsThis research emphasizes that the success in the roll-out of COVID-19 vaccination requires citizens' willingness to participate and their trust in the vaccine's efficacy. Such self-awareness and self-discipline in society can ultimately empower individuals and stabilise the economy. Nevertheless, the implementation of health protocols is still highly required to prevent the spread of new variants of COVID-19.Originality/valueThis is the first study that attempts to construct a VCI which denotes the confidence derived from the administration of full-dose COVID-19 vaccines (an initial vaccine and a second vaccine). The authors further find the impact on cryptocurrency returns. Next, blockchain size is utilized as a new determinant of cryptocurrencies.

Impact of Covid-19 Pandemic on the Investment Behavior of DIIs and FIIs on Indian Debt and Equity Markets

This paper aims to examine the impact of the Covid-19 pandemic on the investment behaviours of both Domestic Institutional Investors (DIIs) and Foreign Institutional Investors (FIIs) in the Indian debt and equity markets. The study is based on the daily time-series data from January 01,2015, to June 03, 2020. The study has constructed three Structural Vector Auto Regression dynamic models to compare the investment behaviors of FIIs and DIIs in both pre-and post-pandemic periods. The results indicate that the Institutional Investors' activities do not significantly impact the equity returns in the Indian markets, which has remained so in the wake of Covid-19. The debt purchases and sales for the DIIs are relatively more inelastic to market returns and reflect the risk-averse investment attitude of DIIs because of the negligible impact of Covid-19. There is a drop in the risk appetite of the FIIs due to a rise in the share of debt holdings in their portfolio in the wake of the Covid-19 pandemic.

PREDICTIVE ABILITY OF FINANCIAL AND NON-FINANCIAL PERFORMANCE FOR FINANCIAL STATEMENT PUBLICATION TIME FRAME: MODERATING ROLE OF COVID-19 PANDEMIC

Objetivo: Este estudo examinou a capacidade de desempenho financeiro e nao financeiro na previsäo do tempo de publicaçao de relatórios financeiros, moderada pela pandemia da COVID-19. Referenciái teórico: A teoria dos sinais postula que a administraçâo desempenha um papel crucial no fornecimento de informaçöes as partes interessadas sobre as condiçöes da empresa (Brigham & Houston, 2001). De acordo com Spence (1973), as empresas estao motivadas a fornecer informaçöes relevantes as partes interessadas. Se as condiçöes de desempenho sao boas, a empresa tende a acelerar o processo de apresentaçao de demonstraçöes financeiras. Por outro lado, se o desempenho for ruim, há uma tendencia a atrasar a publicaçao dos relatórios financeiros. O longo período de tempo para a publicaçao de relatórios financeiros pode indicar más noticias que a empresa tem, de modo que ela ainda tem que publicar as noticias para o público. Scott (2015) sugere que quando os gerentes souberem que há noticias desfavoráveis sobre a condiçao da empresa no futuro, evitarao publicar estas informaçöes ou pelo menos atrasaräo a apresentaçao das demonstraçöes financeiras. Método: O desempenho financeiro foi medido por quatro indicadores: lucratividade, liquidez e solvencia. Enquanto isso, o desempenho nao financeiro variável foi medido pelo indice de boa governança corporativa (GCG) e pela reputaçao dos auditores. O modelo proposto foi testado com base nos dados quantitativos coletados de 156 empresas de manufatura listadas na Bolsa de Valores da Indonesia (IDX) a partir de 2018 e 2020. A análise de regressao múltipla foi realizada para analisar e interpretar os dados. Resultados e conclusao: O resultado indica que a solvencia, a boa governança corporativa e a reputaçao do auditor foram preditores significativos do período de publicaçao do relatório financeiro. Entretanto, a capacidade preditiva de rentabilidade e liquidez no prazo de publicaçao nao foi considerada significativa. Além disso, os resultados mostram que a pandemia da COVID-19 modera a capacidade de rentabilidade e boa governança corporativa na previsao do prazo de publicaçao. Implicates da pesquisa: O indicador de desempenho financeiro e nao financeiro dá resultados diferentes na previsäo do RWPLK das empresas de manufatura na Indonesia. ROA e CR nao sao capazes de prever o RWPLK, mas DER, GCG, KAP sao capazes de prever o RWPLK. O papel da pandemia COVID-19 foi capaz de moderar a capacidade de ROA e GCG em prever o prazo para publicaçao de relatórios financeiros, mas foi incapaz de moderar a capacidade de CR, DER e KAP em prever o RWPLK. Originalidade/valor: O presente estudo fornece a primeira evidencia empírica sobre o papel moderador da pandemia COVID-19 na capacidade preditiva do desempenho financeiro e nao financeiro para o prazo de publicaçao das demonstraçöes financeiras.Alternate :Purpose: This study examined the ability of financial and non-financial performance in predicting financial reports publication time frame as moderated by the COVID-19 pandemic. Theoretical framework: Signal theory postulates that management serves a crucial role in providing information to stakeholders regarding the condition of the company (Brigham & Houston, 2001). According to Spence (1973), companies are motivated to provide relevant information to stakeholders. If the performance conditions are good, the company tend to speed up the process of presenting financial statements. Conversely, if performance is poor, there is a tendency to delay the financial reports publication. The long span of time for the publication of financial reports can indicate bad news that the company has so that it has yet to publish the news to the public. Scott (2015) suggests that when managers know there is unfavorable news about the condition of the company in the future, they will avoid publishing this information or at least delay the presentation of financial statements. Method/design/approach: Financial performance was measured by four indicators: profita il ty, liquidity and solvency. Meanwhile, variable non-financial performance was measured by the index of good corporate governance (GCG) and auditor reputation. The proposed model was tested based on the quantitative data collected from 156 manufacturing companies listed on the Indonesia Stock Exchange (IDX) from 2018 and 2020. The multiple regression analysis was performed to analyze and interpret the data. Results and conclusion: Result indicates that solvency, good corporate governance, and auditor reputation were significant predictors of the time span of financial report publication. However, the predictive ability of profitability and liquidity on the publication timeframe was found to be not significant. Furthermore, the results show that the COVID-19 pandemic moderates the ability of profitability and good corporate governance in predicting the publication timeframe. Research implications: Financial and non-financial performance indicator gives different results in predicting the RWPLK of manufacturing companies in Indonesia. ROA and CR are not able to predict RWPLK, but DER, GCG, KAP are able to predict RWPLK. The role of the COVID-19 pandemic was able to moderate the ability of ROA and GCG in predicting the timeframe for publication of financial reports, but was unable to moderate the ability of CR, DER and KAP in predicting RWPLK. Originality/value: The present study provides the first empirical evidence on the moderating role of the COVID19 pandemic on the predictive ability of financial and non-financial performance for financial statement publication time frame.