Tzachi Zach

Information Externalities Along the Supply Chain: The Economic Determinants of Suppliers’ Stock Price Reaction to Their Customers’ Earnings Announcements

We study the economic determinants of the information externality suppliers experience at the time of their customers’ quarterly earnings announcements (QEAs). We measure the information externality as suppliers’ stock price reaction to their customers’ QEAs. We expect information externalities to arise because the information revealed in customers’ QEAs can revise investors’ expectations about the level of suppliers’ future earnings and cash flows, and or because it resolves uncertainty about those future earnings and cash flows. We find that the information externality experienced by suppliers is increasing in the: (1) magnitude of the new information disclosed at customers’ QEAs; (2) strength of the economic bond between the firms, (3) components of the earnings information disclosed by a customer, (4) level of macroeconomic uncertainty prevailing at the time of customers’ QEAs; and decreasing in suppliers’ earnings persistence. We also find that the information contained in customers’ QEAs leads to both a revision in beliefs about the level of suppliers’ future earnings, as well as to a resolution of uncertainty about such earnings. Our study adds to the literature which seeks to understand the economic factors that lead to cross-sectional differences in earnings informativeness. However, unlike prior studies which have focused on examining the factors that determine “own-firm” stock price reactions to earnings, we identify the economic factors that lead to cross-sectional differences in the informativeness of one firm’s earnings (e.g., a customer’s) to investors of a another, non-announcing firm (e.g., a supplier). Our study also extends prior research by documenting that information externalities are not limited to firms in the same industry but also extend to firms in the supply chain.

The Effect of R&D Inputs and Outputs on the Relation Between the Uncertainty of Future Operating Performance and R&D Expenditures

Consistent with the uncertainty of research and development’s future benefits, prior accounting studies hypothesize and find a positive relation between research and development (R&D) and the variability of future earnings. However, prior research has assumed constant marginal productivity of R&D in the cross-section. We relax this assumption and advance the accounting literature on the informational role of R&D by studying how measures of innovation outputs, namely patent counts and patent citations, which proxy for the economic value of innovation, are related to firms’ future performance. We predict and find that firms’ future operating performance is positively related to the quality of their patents and that this relation is stronger for more productive and innovative firms. We also predict and find that the volatility of future operating performance is negatively related to patent quality and that the relation is stronger for firms with higher R&D expenditures and larger patent portfolios. Overall, firms whose R&D is more productive exhibit higher and less volatile future operating performance. One contribution of our study is that it demonstrates that the relation between R&D expense (i.e., inputs) and future operating performance is better understood by incorporating information about the productivity (i.e., outputs) of a firm’s R&D outlays in the form of patent counts and citations.

The Impact of a Heterogeneous Accrual-Generating Process on Empirical Accrual Models

The cross-sectional approach that is typically used to estimate accrual models implicitly assumes that firms within the same industry have a homogeneous accrual-generating process (AGP). In this article, the authors examine this implicit assumption along three dimensions. First, they argue that the relationship between working-capital accruals and changes in sales is more complex than portrayed by existing empirical accrual models. In addition to sales changes, accruals are also affected by accrual determinants such as firms’ inventory and credit policies. Second, the authors provide evidence that the assumption of a uniform AGP is violated in industries whose firms’ accrual determinants are highly dispersed. Third, they document some implications of violating the assumption of a uniform AGP. Firms in industries with high variations in accrual determinants are likely to have large absolute abnormal accruals. The authors show that the previously documented increase in the absolute level of abnormal accruals over time could be attributed, in part, to the increased heterogeneity in industries with respect to their AGPs.

What Are Analysts Really Good At

Sell-side analysts employ different benchmarks when defining their recommendations. A buy for some brokers means the stock is expected to outperform its industry, while for other brokers it means the stock is expected to outperform the market, or some return threshold. We show that these stated benchmarks have implications for the distribution of recommendations, price reactions to recommendations, and the investment value of recommendations. We conclude that, depending on the question, academics may need to account for the benchmarks when studying analysts’ outputs, and investors may find the benchmarks beneficial in interpreting analysts’ advice.Sell-side analysts employ different benchmarks when defining their stock recommendations. For example, a ‘buy’ for some brokers means the stock is expected to outperform its peers in the same sector (“sector benchmarkers”), while for other brokers it means the stock is expected to outperform the market (“market benchmarkers”), or just some absolute return (“total benchmarkers”). We explore the validity and implications of the adoption of these different benchmarks. Analysis of the relation between analysts’ recommendations and their long-term growth and earnings forecasts suggests that analysts indeed abide by their benchmarks: Sector benchmarkers rely less on across-industry information, and focus more on ranking firms within their industries. We also find evidence that market- and sector-benchmarkers are successful in meeting or beating their benchmark returns, while total-benchmarkers are not. However, we do not find much evidence that investors react differently to recommendations based on the different benchmarks. The research carries implications for the correct understanding and interpretation of sell-side research and its investment value.

Soft Information in Loan Agreements

In this study, we seek to understand whether soft information conveyed by contracting language found in private loan agreements is informative regarding borrower risk. We proxy for credit-risk-relevant soft information using Loughran and McDonald’s uncertainty measure. We first examine initial contract terms and find that, incremental to traditional summary measures of credit risk, increased contractual uncertainty is associated with higher initial loan spreads and a greater likelihood of using dynamic and performance-pricing covenants. We then turn to examine realized credit risk over the life of the loan and find that increased uncertainty is associated with a higher likelihood of future loan downgrades and loan amendments. We corroborate our results on the risk relevance of soft information by showing that the bid-ask spreads of loans trading on the secondary loan market are increasing in uncertainty. Overall, the evidence we provide is consistent with embedded linguistic cues in loan agreements publicly revealing the credit risk assessments of privately informed lenders.