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The purpose of this study is to analyze the predictability of firm level data for determining macroeconomic indicators such as unemployment.

This study uses quarterly GDP and unemployment data manually collected from the Statistical Center of Iran (SCI). Accounting numbers are also collected from the Tehran Stock Exchange library for the 2004-2015 period. Dispersion of earnings growth provides related data about labour reallocation, unemployment change and finally aggregate output. To summarize, this study attempts to examine the effect of these variables using classical and Bayesian approaches.

At a firm level, our results suggest that sectoral shift in previous years is likely to increase labour reallocation in subsequent years. At the macro level, the results reveal that dispersion of earnings growth and labour reallocation has a negative and positive impact on unemployment changes, respectively. However, the study suggests no significant relationship between stock return and unemployment changes. Consequently, we determine that the real estimates of macroeconomic indicators have predictive power because nominal estimates are not statistically associated with firm-level details. Finally, the results obtained from classical and Bayesian approaches suggest similar findings, thus confirming the robustness of our conclusions. Note that, based on Bayesian approach, the nominal reallocation has predictive power in unemployment rate.

The study is the first conducted in a developing country and the results provide important insight into current line of accounting literature.

A large number of topics could legitimately be included under the umbrella title of this article. However, the coverage inevitably reflects the writer's interests, and the paper thus examines the effects of technological change on employment, earnings, and the structure of labour markets. The article has four main sections. The first examines changes in the occupational structure of employment and discusses the structuralist hypothesis that technical progress shifts the occupational demand for labour in such a way as to create permanent unemployment. The second section looks at how technical progress has affected employment and earnings at the level of the industry. The third section takes up the notion of the dual labour market and discusses the extent to which innovation has been an important force generating divisions in the labour market. Finally the implications for government policy are examined.

Previous research has provided mixed evidence on the relative importance of three earnings thresholds that managers seek to achieve: avoiding losses, avoiding earnings declines and avoiding negative earnings surprises. The purpose of this paper is to investigate whether firm‐specific factors influence management's preferences for an earnings threshold.

Logit models are estimated to explore the relationships between firm‐characteristics and management's perceptions of the relative importance of each threshold.

This paper finds that: large firms, firms with high growth prospects and firms with high trading volume are more concerned with avoiding negative earnings surprises, while small firms, firms with low growth prospects and firms with low trading volume are more prone to avoid earnings declines and losses; for firms with high analyst forecast accuracy (relative to a random walk model forecast), avoiding negative earnings surprises is more important than avoiding earnings declines and losses; and firms with low analyst forecast dispersion focus more on avoiding negative earnings surprises and losses, while firms with high analyst forecast dispersion focus more on avoiding earnings declines. Overall, this paper shows that firm characteristics do affect management's perceptions of the relative importance of each threshold.

This study recognizes the cross‐sectional differences in the earnings threshold hierarchy. The results suggest that regulators and practitioners should focus on different thresholds for different types of firms when investigating the mechanisms used to achieve the thresholds.

The accounting literature has traditionally focused on firm-level studies to examine the capital market implications of earnings and other accounting variables. We first develop the arguments for studying capital market implications at the aggregate level as well. A central issue is that diversification makes equity investors at least partially and potentially almost completely immune to several firm-level properties of earnings by holding diversified portfolios. Diversification is particularly important when assessing the welfare consequences of random errors in accounting measurement (imperfect accruals) and, to the extent it is independent across firms, of deliberate manipulation (earnings management). Consequently, some firm-level metrics of association, timeliness, value relevance, conservatism and other earnings properties do not map easily into investor welfare. Similarly, earnings-related risk manifests itself to equity investors largely through systematic earnings risk (covariation with aggregate earnings and/or other macroeconomic indicators). We conclude that the design and evaluation of financial reporting must adopt at least in part an aggregate perspective. We then summarize the literature in accounting, economics and finance on aggregate earnings and stock prices. Our review highlights the importance of studying earnings at the aggregate level.

This study examined the effect of different types of politically connected (PCON) Malaysian firms on analysts' forecast accuracy and dispersion.

The study identified different types of PCON firms according to Wong and Hooy's (2018) classification, which divided political connections into government-linked companies (GLCs), boards of directors, business owners and family members of government leaders. The sample covered the period 2007–2016, for which earnings forecast data were obtained from the Institutional Brokers' Estimate System (IBES) database and financial data were extracted from Thomson Reuters Fundamentals. We deleted any market consensus estimates made by less than three analysts and/or firms with less than three years of analyst forecast information to control for the impact of individual analysts' personal attributes.

The study found that PCON firms were associated with lower analyst forecast accuracy and higher forecast dispersion. The effect was more salient in GLCs than in other PCON firms, either through families, business ties or boards of directors. Further analyses showed that PCON firms—in particular GLCs—were associated with more aggressive reporting of earnings and poorer quality of accruals, hence providing inadequate information for analysts to produce accurate and less dispersed earnings forecasts. The results were robust even after addressing endogeneity issues.

This study found new evidence of the impact of different types of PCON firms in exacerbating information asymmetry, which was not addressed in prior studies.

This study has a significant practical implication for investors that they should be mindful of high information asymmetry in politically connected firms, particularly government-linked companies.

This is the first study to provide evidence of the impact of different types of PCON firms on analysts' earnings forecasts.

This study examines the role of intellectual capital disclosure (ICD) on earnings forecasting by analysts in the pharmaceutical industry in emerging countries, particularly in Indonesia, Malaysia and Thailand. This study specifically examines the role of each component of the ICD on analysts' forecasts, which consists of errors of forecasted earnings, the standard deviation of forecasted earnings and analyst recommendations.

Panel data analysis is conducted using a sample of 17 companies from pharmaceuticals industries in Indonesia, Malaysia, Thailand – Growth Triangle (IMT-GT), which are listed in the Indonesia Stock Exchange (IDX), Malaysia Stock Exchange (MYX) and Stock Exchange of Thailand (SET) from 2010 to 2017. Secondary data is obtained from Bloomberg and Annual report, where they are being analyzed to measure the ICD and gather the control variables.

The results indicate that the three components of ICD, namely human capital disclosure (HCD), structural capital disclosure (SCD) and relational capital disclosure (RCD), insignificantly influence average analysts' consensus recommendation and analysts' earnings forecast dispersion. However, the findings show a significant negative influence of relational capital disclosure (RCD) on analysts' earnings forecast error. In contrast, HCD and SCD have an insignificant impact.

Transparency in disclosing activities related to external parties is essential for the pharmaceutical industry. It is found that relational capital disclosure is the only ICD indicator that can strengthen analysts' profit predictions. Transparency about company activities in maintaining customer satisfaction and activities related to strategic alliances with other organizations are two critical things that can accommodate the accuracy of earnings forecasting from analysts in pharmaceutical companies.

This study contributes to ICD-related research by discussing the financial analyst's response to this voluntary disclosure in the pharmaceutical industry, particularly in Indonesia, Malaysia and Thailand. The selected observation period is seven years, starting one year after the global financial crisis. The results showed that the disclosure of IC is not an exciting thing for financial analysts. In forecasting current earnings, financial analysts are more interested in errors than the previous year's estimates.

The purpose of this paper is to investigate the impact of the introduction of New Zealand's statutory‐backed continuous disclosure regime enacted in December 2002 on the differential disclosure behaviour of New Zealand firms with good and bad earnings news.

This paper examines the level of information disclosure, analyst forecast error and forecast dispersion, abnormal returns and abnormal volumes for firms with good and bad news earnings announcements in a sample period surrounding reforms to New Zealand's continuous disclosure regime.

The authors find evidence that the pre‐announcement information flow was poorer prior to the reform for bad news firms compared to good news firms, in terms of greater analysts' forecast dispersion and a larger abnormal price reaction to the actual earnings announcement. Second, the reform reduced the asymmetry of information flow between good and bad news firms, with the differences in analysts' forecast dispersion and abnormal price reaction dissipating after the reform.

The findings suggest that the reforms to New Zealand's continuous disclosure regime have reduced managers' propensity to withhold bad news and improved the quality of information provided to investors by firms with bad earnings news.

This study improves our understanding of the impact of disclosure reform on the behaviour of managers in a market with relatively low liquidity and less litigation risk in comparison to larger and more developed markets.

The aim of this chapter is to analyze the sources of earnings dispersion between trainees and nontrainees. We stress three mechanisms by which investment in general training may affect wage inequality: directly via participation to a general training program and indirectly via the selection process of trainees or the existence of heterogeneous returns on training. This chapter adopts an approach originally proposed by Fields (2003) but extends it to the breakdown of inequality by population subgroups – those who received training and those who did not. The empirical illustration is based on four French surveys, the 2006 Adult Educational Survey and the 2004, 2005, and 2006 Labor Force Surveys that complement it.

Financial analysts have been found to be overconfident. The purpose of this paper is to study the ramifications of that overconfidence on the dispersion of earnings estimates as a predictor of the US business cycle.

Whether aggregate analyst forecast dispersion contains information about turning points in business cycles, especially downturns, is examined by utilizing the analyst earnings forecast dispersion metric. The primary analysis derives from logit regression and Markov switching models. The analysis controls for sentiment (consumer confidence), output (industrial production), and financial indicators (stock returns and turnover). Analyst data come from Institutional Brokers Estimate System, while the economic data are available at the Federal Reserve Bank of St Louis Economic Data site.

A rise in the dispersion of analyst forecasts is a significant predictor of turning points in the US business cycle. Financial analyst uncertainty of earnings estimate contains crucial information about the risks of US business cycle turning points. The results are consistent with some analysts becoming overconfident during the expansion period and misjudging the precision of their information, thus over or under weighting various sources of information. This causes the disagreement among analysts measured as dispersion.

This is the first study to show that analyst forecast dispersion contributions valuable information to predictions of economic downturns. In addition, that dispersion can be attributed to analyst overconfidence.

Inequality in the distribution of family income in the U.S., which had remained virtually unchanged since the end of World War II until 1968, has increased sharply since then. In contrast, schooling and skill inequality has declined rather steadily over the postwar period. Another notable change over the past 30 years or so has been the widespread diffusion of computers. Using aggregate time-series data for the 1947–2000 period, I find that the largest effects on inequality come from office, computing and accounting equipment (OCA) investment, which accounted for about half of the rise in inequality between 1968 and 2000. The unionization rate is second in importance, and its decline over this period explains about 40 percent of the increase in inequality. The decline in the dispersion of schooling, on the other hand, plays almost no role in explaining the rise in inequality. On the basis of pooled time series, industry regressions for the 1970–2000 period, I also find that investment in OCA is positively related to changes in skill inequality, while changes in the unionization rate are negatively related.