本研究檢測會計師事務所總所審計與分析師盈餘預測行為的相關性。以中國大陸2010年至2015年A股上市公司為研究對象，構造分析師盈餘預測行為的回歸模型，並以分析師追蹤人數、分析師盈餘預測準確度及預測分歧度三種特性進行分析。 研究結果顯示，會計師事務所總所審計與分析師追蹤人數、盈餘預測準確度皆呈顯著正相關，與預測分歧度呈顯著負相關。進一步檢測發現：總所的審計公費更高，經會計師事務所總所審計的企業，分析師更願意對其股票給予較高的投資評級。這也顯示會計師事務所總所付出的努力更多，審計品質更好，因而分析師對其會計資訊信賴程度更高，對該公司之追蹤意願更高，盈餘預測誤差與預測分歧度更低，分析師也更願意推薦其股票。 / The primary objective of this thesis is to explore the association between headquarter office auditors and analysts’ earnings behaviors. I use a sample of firm observations from China during 2010-2015. The main findings can be summarized as follows. I find that firms audited by headquarter office auditors have more analysts following compared to those audited by branch office auditors. Secondly, I find that analysts’ earnings forecasts are more accurate and less dispersed for firms audited by headquarter office auditors than firms audited by branch office auditors. Further analysis indicates that the reason for the above results is that headquarter office auditors exert more effort, measured as audit fees, than branch office auditors. Finally, the empirical results indicate that analysts make more favorable recommendations for firms audited by headquarter office auditors than for those audited by branch office auditors. Overall, the findings suggest that headquarter office auditors have better audit quality and in turn result in more analysts following and issuing higher-quality forecasts and favorable recommendations.

The conduct of effective economic policy faces a multiplicity of macroeconomic challenges, which requires a wide scope of theoretical and empirical analyses. With a focus on the European Union, this doctoral dissertation consists of two parts which make empirical and methodological contributions to the literature on forecasting real economic activity and on the analysis of business cycles in a boom-bust framework in the light of the EMU enlargement. In the first part, we tackle the problem of publication lags and analyse the role of the information flow in computing short-term forecasts up to one quarter ahead for the euro area GDP and its main components. A huge dataset of monthly indicators is used to estimate simple bridge equations. The individual forecasts are then pooled, using different weighting schemes. To take into consideration the release calendar of each indicator, six forecasts are compiled successively during the quarter. We find that the sequencing of information determines the weight allocated to each block of indicators, especially when the first month of hard data becomes available. This conclusion extends the findings of the recent literature. Moreover, when combining forecasts, two weighting schemes are found to outperform the equal weighting scheme in almost all cases. In the second part, we focus on the potential accession of the new EU Member States in Central and Eastern Europe to the euro area. In contrast to the discussion of Optimum Currency Areas, we follow a non-standard approach for the discussion on abandonment of national currencies the boom-bust theory. We analyse whether evidence for boom-bust cycles is given and draw conclusions whether these countries should join the EMU in the near future. Using a broad range of data sets and empirical methods we document credit market imperfections, comprising asymmetric financing opportunities across sectors, excess foreign currency liabilities and contract enforceability problems both at macro and micro level. Furthermore, we depart from the standard analysis of comovements of business cycles among countries and rather consider long-run and short-run comovements across sectors. While the results differ across countries, we find evidence for credit market imperfections in Central and Eastern Europe and different sectoral reactions to shocks. This gives favour for the assessment of the potential euro accession using this supplementary, non-standard approach.

In this master thesis, the impact of forward-looking macroeconomic information under IFRS 9 is studied using fictional data from a Swedish mortgage loan portfolio. The study employs a time series analysis approach and employs vector autoregression models to model expected credit loss parameters with multiple incorporated macroeconomic parameters. The models are analyzed using impulse response functions to study the impact of macroeconomic shocks and the results show that the unemployment rate, USD/SEK exchange rate and 3-month interest rates have a significant impact on expected credit losses. / I detta examensarbete studeras effekterna av framåtblickande makroekonomisk information enligt IFRS 9 med fiktiv data baserad på en svensk bolåneportfölj. Studien använder sig av tidsserieanalys och vektorautoregressionsmodeller för att modellera förväntade kreditförlust-parametrar med flera inkorporerade makroekonomiska parametrar. Modellerna analyseras med hjälp av impulsresponsfunktioner för att studera effekterna av makroekonomiska chocker. Resultaten visar att arbetslöshet, USD/SEK växelkurs och 3-månaders räntor har en signifikant inverkan på förväntade kreditförluster.

Research has validated the contribution of information sharing to performance improvement. It has also suggested that flexibility is a highly important competitive priority for those companies where demand is volatile. Several studies argue that flexibility has been recognized as a key enabler for supply chain responsiveness. However, the impact of information sharing on supplier flexibility is still unexplored, especially for the companies that operate in agile business environments such as in the automotive industry where flexibility is a strategic requirement to manage demand uncertainty. In agile supply chains, such as in the automotive industry, information sharing can play an important role in responding to demand variability. In such settings, the demand volumes generally fluctuate, and hence create production-scheduling problems for the upstream suppliers such as first-tier suppliers. Interestingly, the impact of demand fluctuations on suppliers is higher than that of Original Equipment Manufacturers (OEMs). The aim of this doctoral thesis is to investigate the role of information sharing between OEMs and first-tier suppliers, in enhancing supplier flexibility. Particularly, the research focuses on exploring the relationship between sharing demand schedules and inventory data, and volume and delivery flexibility. The questions on whether information sharing between OEMs and first-tier suppliers affect supplier flexibility remain unanswered. The following research questions have emerged:  RQ1: How does information sharing between OEMs and first-tier suppliers affect the latter's responsiveness to fluctuating demand? RQ2: What is the relationship between information sharing of OEMsʼ demand forecasts and inventory data, and suppliers’ volume and delivery flexibility? RQ3: What factors should OEMs consider to improve the sharing of demand forecasts with suppliers? The empirical part of this thesis comprises three individual studies that constitute the empirical foundations of the research problem. Each study analyzes one research question using its own methodological approach. Hence, different research methods for collecting and analyzing data were used to address the research questions. Applying different research methods is deemed advantageous because it allows for methodological rigorousness in this doctoral thesis. This thesis contributes to the body of knowledge in three dimensions—theory, method, and context. First, it contributes to the academic field of operations and supply chain management by developing a model to explain how information sharing could affect suppliers’ delivery performance. The model provides a measurement scale to measure the level of information sharing between OEMs and suppliers, and its impact on suppliers’ delivery flexibility. Second, this thesis contributes to the methods by using state-of-the-art techniques, which is partial least squares structural equation modeling (PLS-SEM) including consistent PLS, and applying advanced concepts to empirically test the proposed model. Third, this thesis has a managerial contribution to examine the concept of information sharing and flexibility at the supplier level. Investigating the problem at the supplier level may enable managers to improve short-term decisions, such as production scheduling decisions, internal production, and inventory processes, and evaluate collaboration practices with OEMs. This doctoral thesis is organized in a monograph format comprising five chapters: Introduction, Literature review, Methodology, Empirics, and Conclusion. As an outcome, several scientific articles have emerged from this thesis and have been submitted for consideration for publication in peer-reviewed journals and international conferences in the field of operations and supply chain management. These articles are listed and appended at the end of this dissertation. / <p>QC 20160302</p>

Master of Arts / Department of Economics / Lance J. Bachmeier / This thesis examines the properties of two short-term interest rates: the federal funds rate and the rate of return on 90-day Treasury securities (T-Bills). Findings indicate strong evidence of cointegration among the two series. This result leads us to consider whether future movements in T-bill returns are predictable using the same methods used to predict the target federal funds rate. The “Taylor Rule,” introduced by Taylor (1993), assumes the Federal Reserve considers inflation and the output gap in their deliberation of how to adjust the federal funds target rate. We do an in-sample analysis followed by an out-of-sample forecasting comparison. Findings show that, in addition to inflation and the output gap, the unemployment rate and stock market contain valuable information for forecasting future T-bill rates.

達成或超越分析師的盈餘預期為公司重要目標之一，市場包括投資人或分析師對於公司達成盈餘預期目標的反應，一直為學界所關心。文獻發現達成盈餘預期目標的公司，確實享有較未達成目標者更高的股價報酬，顯示市場對此持有正面的反應，因為達成目標的公司，未來將有較佳的獲利能力。本文延伸文獻之探討，進一步考量經濟環境因素---景氣反轉，在這一議題上可能扮演的角色，亦即試圖探討景氣反轉時市場對公司達成或超越分析師盈餘預期的反應，以及達成盈餘預期目標的資訊內涵，會如何受到景氣反轉因素的影響。 實證結果發現達成或超越分析師盈餘預期事件所帶來的股價反應，不會受到景氣由上往下反轉的影響而有所差異，但分析師對此等事件的反應則會隨景氣由上往下反轉而更為強烈，在景氣由下往上反轉時則較無差異；至於此等事件所隱含公司未來將有較佳獲利能力的資訊內涵，雖不會隨著景氣由上往下反轉而有所差異，卻會隨著景氣由下往上反轉而更為增強。 / Meeting or beating analysts’ earnings forecasts is an important goal for the management to achieve. As a result, the market reaction to the meeting of earnings expectations has been intensively explored. In general, the meeting of earnings expectations signals brilliant future profitability to the investors. Following this line of research, this study further investigates the effect of business cycle on the relationship between market reaction and the meeting of earnings expectations. We find that the stock returns of firms meeting or beating analysts’ forecasts are not affected by the sudden downturn of the economy. On the contrary, analysts’ response to such events becomes stronger in the economic downturn though it remains the same when the economy rebounds. As for the issue of information content, meeting earnings expectations is more informative when the economy rebounds from recession but not in the downturn of the economy.

強制性財務預測揭露制度已實施十多年，惟財務預測品質不佳、管理當局刻意操縱財務預測以影響股價等問題遲遲無法解決，致金管會乃決定自2005起廢止舊制，改採自願性財務預測揭露制度。本次改革除符合國際做法之外，並期望能達到降低公司財務預測成本、提高預測準確度，以及健全預測資訊公開之環境。 2005年為實施自願性財務預測揭露制度之第一個年度，當年上市（櫃）公司中，只有約6%的公司自願公開其財務預測。本研究認為，對投資人而言，財務預測既為有用資訊，為何願意公開財務預測的公司卻如此少呢？故本研究欲辨認左右公司是否公開財務預測行為之因素。 本研究設立七項與管理當局自願性揭露財務預測有關之決定因素─內部人持股比率、資本結構、資金需求、經營績效、盈餘波動性、權益資金成本，以及外資持股率，並以公司規模、產業、負債對權益比率為控制變數。研究樣本為2005年之上市(櫃)公司，將其分成兩組，ㄧ組為當年度自願揭露財務預測之公司，另ㄧ組則為當年度未曾揭露財務預測之公司，運用logit進行迴歸分析。 實證分析結果顯示，揭露與不揭露財務預測公司之主要不同特質，在於：公司過去經營績效之好壞及外資對公司之持股比率。過去經營績效較佳之公司，其主動揭露財務預測資訊給外界之機率較高；外資持股比率越高之公司，其主動揭露財務預測給外界之機率較高。 / This study examines the factors that affect managers to disclosure financial forecasts. Seven potential factors were compared for a sample of firms that reported forecasts and another sample of firms that did not release this information. The seven factors are: (1) the proportion of inside ownership, (2) capital structure, (3) the demand for external finance, (4) the business performance, (5) earnings volatility, (6) the cost of equity capital, (7) the proportion of foreign ownership. There are three control variables, including size, industry and the ratio of debt to equity. The findings report that the better the past business performance is, the more the probability that the manager will voluntarily disclose financial forecast is. The findings also report that the higher the proportion of foreign ownership is, the more willing the manager is to voluntarily disclose financial forecast.

分析師扮演著公司與投資大眾之間的資訊中介者角色。本文旨在探討企業研發支出對分析師預測品質的影響，以及企業聘雇屬於產業專家會計師是否能夠緩和研發支出所引發的盈餘管理及代理問題，並進而改善分析師預測品質。本文援引Balsam (2003)之定義，計算會計師事務所於各產業之市場佔有率(auditor industry market share)。作為產業專家之代理變數。實證結果發現：(1)分析師離散性與整合分析師間私有利益的程度，與公司研發費用多寡有關。研發費用愈高的公司，分析師的離散程度及整合分析師間的私有利益也愈高；(2)透過產業專家查核，可以緩和研發費用支出所引發的盈餘操縱及代理問題，因此研究發展費用透過產業專家會計師查核，可以提升企業的會計盈餘資訊品質，以降低分析師盈餘預測的離散程度及降低分析師間整合私有資訊的利益。 / Analysts, as an informational intermediary, produce research reports that include forecasts of future earnings, thus fulfill an important role in capital market. The objective of this paper is to investigate the association between analyst forecast’s quality and firm’s R&D expenditure. Recent work has hypothesized that intangible assets affect analyst forecast’s quality. Extending this literature, we hypothesized that firm seek to reduce the degree of earnings’ management and agency’s cost from R&D expenditure by retaining high quality auditor firms, auditor industry expertise, and then increase analyst forecast’s quality. We measure auditor industry expertise based on Balsam (2003). We find that more R&D expenditure increases analyst forecast’s dispersion and enhances the benefits of aggregating individual analysts’ forecasts. Consistent with our hypothesis, we document that auditor industry expertise can mitigate the degree of earnings’ management and agency’s cost from R&D expenditure. We also find that firms retaining auditor industry expertise are more likely to enhance the accounting information quality, decrease analyst forecast’s dispersion, and eliminate the benefits of aggregating individual analysts’ forecasts.

本研究以I/B/E/S中2004至2005年所有美國公司為樣本，依財務分析師盈餘預測值與所有財務分析師盈餘預測平均值之差異程度，將財務分析師分類為大膽或膽怯的財務分析師，並依財務分析師盈餘預測發布之時點將財務分析師分類為領導型或從眾型財務分析師。針對財務分析師盈餘預測行為大膽及領導特性，探討時效性領導型財務分析師之盈餘預測是否會較大膽，並進一步研究大膽的財務分析師其盈餘預測準確度是否較高，以及時效性之領導型財務分析師其盈餘預測準確度是否較高。 研究結果發現時效性之領導型財務分析師其盈餘預測行為會較大膽，但大膽的財務分析師其盈餘預測準確度較低，且時效性之領導型財務分析師其盈餘預測準確度並未出現較高的現象。 / Security analysts can be characterized as bold or herding based on the absolute distance between their earnings forecasts and the consensus forecast. Security analysts can also be classified as lead or following based on the timeliness of their earnings forecasts. Based on I/B/E/S annual earnings forecasts of all American companies during the period of 2004-2005, this study addresses the association between bold and lead and the relation between bold forecast and forecast accuracy. In addition, the relation between lead forecast and forecast accuracy is investigated as well. It is shown that lead analysts are bolder than following analysts and boldness likelihood increases with the frequency of analysts’ forecast and declines with the analysts’ prior accuracy. Further, bold analysts’ earnings forecasts are less accurate than herding analysts’ and lead analysts’ earnings forecasts are less accurate than following analysts.

預測技術是一個不斷變動的領域，本研究提出一個高彈性的預測模型應用框架，供使用者開發各種預測系統，且使用者能夠很容易的將新的預測技術增加到系統之中。本研究先分析現有預測模型的建構過程，提出一共通流程。並依此共通流程定義應用框架，該框架可用以產生各種實際的預測系統。此應用框架具備了高度的彈性，除了在流程上可整合OASIS的WS-BPEL流程描述語言外，且可整合各種不同的預測技術所需的運算方法與資料。 / With the rapidly changing forecast technique, this paper introduces a flexible application framework to develop different forecast systems. When you develop a system by this framework, you can add a new forecast technology easily. This paper provides a common process for model building by analysis exiting processes　and use this common process to develop application framework. In addition to using an XML-based language, Web Services Business Process Execution Language（WS-BPEL）, to describe the details of model building process, this framework can integrates methods and data from different forecast technologies by defining method and data configuration.