Voluntary Disclosure, Moral Hazard, and Default Risk

Avoiding Distortion in Corporate Valuation Litigation: An Application of Discounted Cash Flow

This article develops a contingent claim model to price a default-risky, catastrophe-linked bond. This model incorporates stochastic interest rates and more generic loss processes and allows for practical considerations of moral hazard, basis risk, and default risk. The authors compute default-free and default-risky CAT prices by using the Monte Carlo method. The results show that both moral hazard and basis risk drive down the prices substantially; these effects should not be ignored in pricing the CAT bonds. The authors also show how the prices are related to catastrophe occurrence intensity, loss volatility, trigger level, the issuing firm's capital position, debt structure, and interest rate uncertainty. INTRODUCTION Property-liability insurance companies traditionally hedge their low-loss frequency, high-loss-severity catastrophe risks by buying catastrophe reinsurance contracts. The traditional reinsurance and catastrophe insurance options, which trade in the Chicago Board of Trade (CBOT), are asset hedge instruments for insurers' or reinsurers' catastrophe risk management. A recent innovation in catastrophe risk management is the catastrophe (CAT hereafter). The CAT which is also named as an Act of God bond or insurance-linked bond, is a liability hedge instrument for insurance companies, for which there have been many successful CAT issues recently. (1) CAT provisions have debt-forgiveness triggers whose generic design allows for the payment of interest and/or the return of principal forgiveness, and the extent of forgiveness can be total, partial, or scaled to the size of loss. Moreover, the debt forgiveness can be triggered by the insurer's (or reinsurer's) actual losses or on a compos ite index of insurers' losses during a specific period. The advantage of a CAT hedge for (re)insurers (insurers, hereafter) is that the issuer can avoid the credit risk that may arise with traditional reinsurance or catastrophe-linked options. The CAT bondholders provide the hedge to the insurer by forgiving existing debt. Thus, the value of this hedge is independent of the bondholders' assets, and the issuer has no risk of nondelivery on the hedge. However, from the bondholder's perspective, the default risk, the potential moral hazard behavior, and the basis risk of the issuing firm are critical in determining the value of CAT bonds. The moral hazard behavior occurs when the insurer's cost of loss control efforts exceeds the benefits from debt forgiveness. That is, the insurer has an incentive to pay the claims more generously when the loss amount is near the trigger set in the debt-forgiveness provision. Doherty (1997) pointed out that moral hazard results from less loss control efforts by the insurer issuing CAT bonds because these efforts will increase the amount of debt that must be repaid. Bantwal and Kunreuther (1999) also noted the tendency for insurers to write additional policies in a catastrophe-prone area, spending less time and money in their auditing of losses after a disaster. The moral hazard behavior may increase the claim payments at the expense of the bondholders' coupon (or principal) reduction and affect the price. Another important element that needs to be considered in pricing a CAT is the basis risk. The CAT bond's basis risk refers to the gap between the insurer's actual loss and the composite index of losses that prevents the insurer from receiving complete risk hedging. The basis risk may cause insurers to default on their debt in the case of high individual loss but low index of loss, and therefore affects the price. A tradeoff indeed exists between basis risk and moral hazard. If one uses an independently calculated index to define the CAT payments, then the insurer's opportunity to cheat the bondholders is reduced or eliminated, but basis risk is created. Doherty (1997) and Belonsky (1998), among others, have looked into the effect of basis risk and moral hazard, but not from the perspective of pricing. …

The literature about capital structure is very dense but this density does not lead to establish a clear relation between capital structure and firm value. The seminal work of Modigliani and Miller (1958) states that under perfect market conditions, the capital structure choices are irrelevant to the firm value. This proposition cannot hold when market frictions are introduced in the analysis. From a theoretical standpoint, two main streams of models can be distinguished. First, trade-off models examine the existence of an optimal repartition between debt and equity. They are based on the hypothesis that the cash flows cannot be fully and symmetrically returned to every investors' type because of bankruptcy costs, corporate and individual taxes and characteristics of the output market (level of competition, production techniques and product specificities). Under these circumstances, firms can gain value in managing their capital structure. The repartition between debt and equity is said to be optimal when it maximises the firm value. However, this relation remains difficult to test empirically. The second theoretical stream is based on the hypothesis that market frictions prevent individual investors and market intermediaries to re-design efficiently and costlessly any financial assets. Therefore, firms have an incentive to issue specific securities to minimise the market imperfections impact on their value. Information asymmetry, agency costs, timing, flotation methods and underwriter's certification become the main determinants of the capital structure choices and they are better suited to explain the impact of these choices on the firm value. Unfortunately, the empirical literature lacks to clearly relate explanatory variables to the theory they should refer to. The dissertation proposes two empirical studies that examine the relation between equity financing and firm value, one at the announcement of the equity offering, the other over a long-term horizon. One contribution is to introduce the intended use of the proceeds as a discriminating variable to separate offerings realised in order to finance a specific investment project from those made to improve the capital structure. In both frameworks (short-term after the offering announcement and long-term post-issue horizon), the results in terms of valuation effect are sensitive to the issuer's type. A negative impact is observed but it is restricted to issuers that finance a new investment project. This valuation effect is explained by information asymmetry and timing on the short-run and by model uncertainty on the long-run. It is caused by an expected decrease in future earnings since financial analysts adjust their earnings forecasts downwardly short after the announcement or over a longer-term horizon. One explanation could be that investment projects financed with equity are, first, high-risk with a negative net present value and second, the market is unable to correctly estimate the impact on the firm value at the issue announcement. It needs time to infer the true model parameters so that it may adjust its anticipation about the stock prices correctly. Re-balancing the capital structure has no significant impact on the firm value. The main conclusions can be summarised as follows. First, the intended use of the proceeds allows to differentiate equity issue in terms of valuation effect and of the theories that explain this valuation effect. Second, valuable private information is revealed at the offering announcement. Third, the long-term stock under-performance after the offering is not due to investors' irrationality but to model uncertainty. Fourth and finally, almost half of the equity issues are made in order to improve the capital structure, which is consistent with the American and European CFOs' opinion that their financial policy is mainly driven by the concern of preserving their financial flexibility. Our results show that working on that financing flexibility has no impact on the firm value, as predicted by Modigliani and Miller (1958).

We examine how the information in public signals (e.g., earnings, analysts’ forecasts) affects firms’ voluntary disclosures. We consider levered firms and information structures such that investors update their beliefs about both the mean and variance of the firm’s cash flows. We predict that firms that, conditional on the public signal, have a higher default risk are less likely to disclose. For firms with low ex ante default risk, larger positive surprises following the public signal initially increase the disclosure likelihood because they indicate a higher mean of cash flows. However, too large positive surprises may reduce the disclosure likelihood of these firms, because the larger surprise is also indicative of higher variance and, thus, higher probability of default. Symmetrically, larger negative surprises may increase disclosure for firms with high ex ante default risk, despite the more pessimistic inference about the mean, because the higher variance makes it more likely that these firms avoid default. Extending our analysis to multiple analysts’ forecasts, we predict that not only consensus, but also dispersion affect firms’ disclosure likelihood. Consensus conveys information about the mean and variance of cash flows, whereas dispersion is informative about the precision of analysts’ signals, which in turn affects the information content of forecasts. This paper was accepted by Suraj Srinivasan, accounting. Funding: D. Lee-Lo gratefully acknowledges financial support from the Accounting Research Center at Kellogg.

The Economic Function of Underfunded Pension Plans

Corporate social responsibility (CSR), capital structure, and stock prices have garnered significant attention due to their potential impact on a firm's overall value. Corporate social responsibility involves a company's commitment to ethical and sustainable practices, extending beyond profit generation to encompass social and environmental considerations. On the other hand, capital structure reflects a company's financing composition, encompassing the balance between debt and equity. Stock prices reflect the market's perception of a company's worth and performance. This research aimed to analyze the influence of corporate social responsibility, capital structure, and stock prices on firm value within the banking sub-sector companies during the period 2017-2021. The study utilized panel data regression as its analytical technique. The sample was selected using purposive sampling from secondary data, specifically financial reports. The analysis included 33 companies observed over a 5-year period, resulting in a total of 165 data points for the investigation. Hypothesis testing was conducted using the Eviews series 9 application. The findings from the tests indicated a statistically significant simultaneous impact of corporate social responsibility, capital structure, and stock prices on firm value. However, the research revealed that corporate social responsibility, when assessed independently, did not exhibit a statistically significant impact on firm value. Conversely, the analyses demonstrated that both capital structure and stock prices had a statistically significant partial effect on firm value.

In this paper, we investigate how an electricity capacity market design may encourage generators to exaggerate their available capacity. In order for an analytical approach, a two player game model is introduced. We focus on two pure strategy Nash equilibria: an equilibrium at which generators offer their true capacities, and an equilibrium at which generators offer exaggerated capacities. The latter case is caused by asymmetries of information between players and so called 'moral hazard' in terms of the economics literature. This paper shows that, considering practical electricity markets, the moral hazard case is highly probable. Moreover, it is shown that, with the considered capacity market design in the real world, the better the electricity energy market performs, the higher the risk of moral hazard becomes.

Background: The dynamic interplay between corporate financial strategies, particularly capital structure and dividend policies, significantly influences firm value in the manufacturing sector.Knowledge Gap: While previous research has explored the direct relationships between capital structure and firm value, less attention has been paid to the moderating effects of dividend policy, profitability, and Good Corporate Governance (GCG) in this context. Aims: This study aims to assess the moderating roles of dividend policy, profitability, and GCG on the relationship between capital structure and firm value. Results: The findings indicate that dividend policy, profitability, and GCG significantly moderate the relationship between capital structure and firm value, suggesting that firms must balance dividend distribution with their capital structure decisions. Novelty: This research contributes to the existing literature by integrating dividend policy and GCG into the analysis of capital structure's effect on firm value, addressing previously overlooked aspects. Implications: The study underscores the importance of prudent dividend policies and robust corporate governance in enhancing firm value, offering valuable insights for managers and investors aiming to optimize financial performance in the competitive food and beverage manufacturing sector. Highlights : Moderating Effects: Dividend policy, profitability, and GCG significantly moderate the relationship between capital structure and firm value. Financial Balance: Firms must balance dividend distribution with capital structure decisions to enhance overall value. Managerial Insights: The findings provide crucial insights for managers and investors to optimize financial performance in the food and beverage sector. Keywords: capital structure, dividend policy, firm value, profitability, Good Corporate Governance

The board of directors is one of the components of corporate governance used by the company to improve the firm's performance both in the long and short term so that the characteristics of the board become one of the key factors to running a good governance system for the company, even though having a good board composition is not always makes the company have a good performance because of the conflict of interest that occurs between the principal and the manager of the company so that there is a need for an in-depth study of the impact of capital structure on company performance. This study attempts to assess specifically the characteristics of the board (board size, board diversity, and audit committee) owned by the company to capital structure, then confirmed the effect of capital structure on firm performance and firm value by using ROE for performance and Tobin’s Q for firm value. Was used in the study sample 25 a company that had always entered into the LQ45 index within a time frame of 2015-2019. The technique of analysis that was used in this study was Path Analysis. The results of the testing of hypotheses found that board size and audit committee had a positive impact on capital structure, while board diversity had a negative effect on capital structure, then capital structure had a positive effect on firm performance, otherwise, the capital structure had a negative effect on firm value

General Background The intense competition in the industrial sector necessitates a focus on maximizing firm value to attract investors. Specific Background Profitability, liquidity, and company growth are key determinants of company value, with capital structure playing a crucial financial role. Knowledge Gap Prior studies show conflicting results regarding the direct influence of these financial ratios on firm value, creating a need for a clearer causal model. Aims This study examines the mediating role of capital structure in the relationship between profitability, liquidity, company growth, and firm value in the Indonesian Food and Beverages sector (2019-2022). Results Findings show that while profitability directly affects firm value, liquidity and company growth do not. Crucially, capital structure successfully mediates the relationship between all three independent variables and firm value. Novelty This research contributes by incorporating company growth and capital structure as a mediator to reconcile the existing empirical inconsistencies. Implications The results highlight that optimal capital structure management is vital for the F&B sector, proving to be the essential link for profitability, liquidity, and growth to ultimately increase company value. Highlights Profitability is the only variable with a direct positive effect on firm value. Capital structure successfully mediates the link between all independent variables and firm value. Liquidity and Company Growth require capital structure to positively influence firm value. Keywords: Capital Structure, Profitability, Liquidity, Company Growth, Company Value

Do higher value firms voluntarily disclose more information? Evidence from China

PurposeThe purpose of this study is to examine whether the level of voluntary disclosure affects firm value in the Chinese capital market. It also investigates whether voluntary disclosure and the values of Chinese firms are influenced by the global financial crisis (GFC).Design/methodology/approachThe study used a sample of 714 firm‐year annual reports of listed companies on the Shanghai and Shenzhen Stock Exchanges over a period of five years from 2005 to 2009 and adopt a two‐stage OLS (2SLS) procedure.FindingsIt is found that the extent of voluntary disclosure has improved in China during the period studied. The multiple regression results indicate that more voluntary disclosure does not create value for Chinese firms. It is also observed that multinational ownership, non‐executive directors, and audit committee presence are positively and significantly associated with voluntary disclosure. Furthermore, the study reports that state and individual ownerships are negatively associated with firm value while multinational ownership and liquidity have a positive significant association with firm value. During the financial crisis, voluntary disclosure continues to increase, however, firm value has decreased.Originality/valueUsing data from the Chinese market, the study fills a research gap by examining the value relevance of voluntary disclosure and tests whether the Global Financial Crisis has influenced voluntary disclosure levels and Chinese firms' values.

At the national level, the property industry has a considerable influence. The rapid growth of the property industry will have an impact on other industries. Examples include the material, logistics and service industries, as well as the banking industry through KPR (House Ownership Credit) which will have an impact on job creation and the economy. growth in the country. This study aims to determine the effect of Asset Structure, Business Risk, Profitability, Company Size and Capital Structure on Firm Value (PBV). The period of this research is 5 (five) years, namely 2015 to 2019. This study uses panel data regression analysis. The population of this study includes property and real estate companies listed on the Indonesia Stock Exchange (IDX) for the period 2015 – 2019. The results of this study indicate that the asset structure, business risk, profitability, firm size and capital structure have a simultaneous effect on firm value. Profitability and Capital Structure variables have a positive and significant effect on firm value. Asset structure, business risk, and firm size have no effect on firm value. This study contributes to testing and proving signaling theory and firm value on profitability and capital structure that affect firm value. and the size of the company has no effect on the value of the company. This study contributes to testing and proving signaling theory and firm value on profitability and capital structure that affect firm value. and the size of the company has no effect on the value of the company. This study contributes to testing and proving signaling theory and firm value on profitability and capital structure that affect firm value.

Previous articleNext article FreeCommentOlivier BlanchardOlivier BlanchardPeterson Institute of International Economics and NBER Search for more articles by this author Peterson Institute of International Economics and NBERPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreThis is an extremely ambitious paper. The Greek drama is one of the most complex macroeconomic developments of the last 10 years. Before I read the paper, my tight prior was that DSGE models were not at a stage where they could handle the relevant complexity. After reading the paper, my posterior is substantially more favorable. In the right hands, DSGE models can shed light even on such complex developments and, while they may not deliver definitive answers, they can lead to a much more interesting discussion. I have learned a lot from the paper.I have organized my discussion as follows. First, I go through the many mechanisms at work when a country confronts the end of a boom under fixed exchange rates (here, a common currency). My purpose is to show the many dimensions of the adjustment process. Then, I examine how close the DSGE model captures the relevant mechanisms, what the model tells us about Greece, and whether we should believe its conclusions.The End of Booms under Fixed Exchange RatesBy the end of a boom, a country operating under fixed exchange rates typically suffers from three related imbalances. The first is overvaluation, the second is a large current account deficit, and the third is high debt. Debt may be private or public. Households may have borrowed too much to buy houses or simply to increase consumption; firms may have borrowed too much to finance investment; and the government may have gone on a spending spree, leading to large deficits and a large increase in public debt.All three imbalances were very much present in Greece at the start of the crisis. Average output growth from 1996 to 2008 was a high 4%. Average inflation (measured by the CPI) was also 4%, so 2% above the average euro inflation rate, leading to steady real appreciation. In 2008, the current account deficit was equal to 14% of GDP. The fiscal deficit was 14.5% of GDP, and public debt stood at 108% of GDP.Booms Come to an End in Two WaysFirst, They Can Die of Old AgeWhile the country can still borrow abroad, the factors behind the boom fade or reverse. The high real exchange rate implies low external demand, and internal demand slows down or even decreases. This may be because reality takes over and expectations of a bright future are revised downward, leading to lower demand. Or, the accelerator effect behind the housing boom or the increase in durable goods comes to an end. Or, the government embarks on fiscal consolidation. All of these lead to a slump and an increase in unemployment.This starts a typically painful process of adjustment. Relative prices have to adjust, competitiveness has to be restored, and the current account deficit has to be reduced. Under fixed exchange rates, this has to happen through a decrease in domestic prices relative to those of competitor countries. Consider the steps in turn:The best adjustment path, if it can be achieved, is to reestablish competitiveness through higher productivity growth. Thus, the frequent call for structural reforms by the European commission or the IMF. The political room for major structural reforms in the middle of a slump is, however, limited. De facto, most of the adjustment process has to happen through the adjustment of nominal wages.Short of social pacts, which are nearly never seen, and short of a coordinated decrease in wages and prices, unemployment is what puts downward pressure on nominal wages; how strong the pressure is depends on the degree of nominal and real wage rigidities, reflected not only in the strength of the response of nominal wages to unemployment, but also the relevance of the zero lower bound on wage decreases.The decrease in wages has then to pass through to prices. The passthrough depends on the market structure, for example, on whether exporting firms are price takers or price makers in foreign markets. One of the surprising features of adjustment within the Eurozone has been the limited pass-through from unit labor costs to prices. An interesting hypothesis is that firms, squeezed for profits because of the decrease in output, and more financially constrained because of tight credit supply, have decided to increase current profits at the expense of future profits. Whatever the reason, incomplete pass-through has slowed down the improvement in competitiveness and the improvement in external demand.The improvement in relative prices then leads to an increase in external demand. Here again, many elements are at play. The size of the export sector is clearly crucial: the more closed the economy, the smaller the effect. The nature of exports is also essential: the elasticity of demand for tourism or for olive oil may be quite different from the elasticity of demand for cars.Even if external demand improves, internal demand may be adversely affected by the adjustment process. Lower inflation—or even deflation in the current context—leads to higher real interest rates and thus lower spending. Deflation also increases the value of the debt. In the context of high debt to start with, this may slow or even derail the adjustment. The improvement in external demand may be more than offset by a decrease in internal demand.Why did I go through all these steps? To make the point that, even if there had not been a sudden stop in Greece, there was a need for a large adjustment process, and that process would likely have been long and painful. Given that there was a sudden stop, we do not know what would have happened, but we can look at the case of Portugal. Portugal’s boom ended in 2001, and, six years later, by the time the financial crisis started, little adjustment had taken place. Unemployment had increased from 4% in 2001 to 7.7% in 2007; average productivity growth over the period was less than 0.2%. Unit labor costs had further increased relative to the euro by 13%, and the current account deficit had further increased, from 5% to 10%. Many of the structural characteristics of Portugal are shared by Greece, among them a narrow export base and a slow adjustment of nominal wages. There is little reason to think that, absent the sudden stop, things would have turned out much better in Greece than they did in Portugal in the first half of the first decade of the twenty-first century.The Other Way in Which Booms End Is with a Sudden StopCreditors start having doubts about the solvency of some of the debtors. They ask for large spreads, or they cut lending altogether. Not all sudden stops are the same. The nature of the debtor matters:The sudden stop may affect the governmentWhat combination of public debt and deficits trigger doubts is hard to predict: debt sustainability is a probabilistic concept, and probability is typically hard to assess. The possibility of self-fulfilling liquidity runs makes it even harder to predict whether and when investors will be reluctant to roll over debt and ask for higher spreads. When the doubts are triggered and spreads rise, what was a difficult fiscal situation becomes intractable. What happens next varies depending on restructuring and on outside help. If the country is on its own, wants to maintain parity, and does not want to restructure its debt, the outcome is an extreme fiscal consolidation, with its predictable adverse effects on output. If creditors agree to a debt restructuring, the pressure to adjust is smaller. And if the country gets into a program with the IMF or other official creditors, outside funds can help smooth the adjustment. In most cases, the outcome is likely to be a strong fiscal consolidation, with its attendant effects on output.This discussion is clearly relevant for Greece. Worries about public debt sustainability led to an increase in interest rates, and by May 2010, the starting date of the first Troika program, the 10-year yield had reached 9%. By January 2012, the yield reached a peak of 35%. It would be wrong, however, to assume that the high rates on the secondary market were the main driver of fiscal policy. From May 2010 on, Greece had access to official financing at much lower rates, and rates on the secondary market were de facto irrelevant. What determined the adjustment of fiscal policy was the amount of financing provided by the program. While very large, namely 110 billion euros for the first program in 2010 and another 130 billion euros for the second program in 2012 (relative to a GDP of about 200 billion euros), it still required a very dramatic fiscal consolidation.Debt restructuring was delayed, taking place only in 2012, leading to a haircut of about 50%, and reducing the debt by about 100 billion euros. One issue is how costly this delay was to Greece, and how much it worsened the adjustment. The answer depends very much on the cost of public debt overhang on private demand. This is another dimension of adjustment that is important, but poorly understood.The Sudden Stop May Affect BanksHere again, solvency and liquidity issues are likely to combine. The slump decreases the value of the assets. Worries about solvency lead depositors and other creditors to take out their funds. Again, the possibility of self-fulfilling liquidity runs introduces substantial uncertainty as to whether and when banks will survive. Even if they do, lower capital lead to a sharp contraction of credit. To the extent that banks hold sovereign bonds, and investors believe that the state will bail out the banks, “doom loops,” interactions between doubts about public debt sustainability and doubts about bank solvency, can slow or derail the adjustment.The decrease in liabilities of Greek banks was more of a slow stop than a sudden stop. Demand deposits did not decrease much until 2011, although deposits with maturity up to a year did. When currency risk became more acute, and demand deposits starting decreasing, it was more like a walk than like a run. Also, foreign banks did not withdraw funds to their Greek subsidiaries; indeed, they initially increased them. And when Greek banks needed to borrow, they were able to get funds first from the ECB, and then, when eligible collateral became scarce, from the Greek central bank through ELA. Just as for the government, the rates at which Greek banks could borrow were not the market rates, but rather the low rates charged by the ECB, and the slightly higher rates charged by the Greek central bank. Nevertheless, increasing non-performing loans due to slump, and the resulting decrease in capital, led to a sharp contraction in credit supply.Finally, the sudden stop may come from doubts about the peg, or in the case of a common currency, the perception of a positive probability of exit and depreciation. Even if foreign creditors, official or private, continue to lend at low rates in terms of foreign currency, the implicit interest rate facing borrowers can increase substantially. National deposit insurance, which offers protection against losses in domestic currency, does not offer protection against a depreciation, so depositors have an incentive to run. Beyond interest rate effects, the option value of waiting increases and is likely to lead to lower investment. The adjustment process can again be derailed.Whenever the adjustment leads to a large decline in output, the perceived probability that the country will give up the peg increases. Indeed, this has been the case in Greece. Both in 2012, and then again after the election of Tsipras in 2015, the perceived probability of Grexit increased. Anecdotal evidence (I do not know of formal empirical work on it) suggests that the effects on activity were substantial. Withdrawals of bank deposits accelerated. Investment decreased further. As the paper rightly emphasizes, perhaps the most striking number of the Greek crisis is the decrease in the ratio of investment to GDP, from a peak of 26% in 2007 to 9% in 2015.Greece and the DSGE ModelI insisted intentionally on the complexity of the adjustment mechanism. The purpose of a model, even a DSGE model, is not, however, to capture all the intricate details, but the essential features of the mechanisms at work and to focus on a few central questions. In the case of Greece, I see three central questions: 1. From 2008 to 2015, output decreased by about 18%. What was the role of fiscal consolidation, a question that has been at the center of the main controversies?2. What other factors played a role in explaining the decline in output?3. Given the situation Greece was in at the start of the crisis, how bad did the adjustment have to be anyway? Does the DSGE model presented in the paper convincingly answer these three questions? My answer is “not yet.” But it yields a rich discussion and a structure to build on. Let me develop these arguments, starting with a discussion of the specification and estimation of the model.There is no question that the specification of the model represents major progress. The model has the essential features needed to answer the questions above. It has two goods, domestic and foreign, so we can think about relative price adjustment. It has nominal rigidities, so the adjustment is slow. Rather than being a representative agent model, it has savers and borrowers, so one can think about financial intermediation. It has intermediation by banks. It allows for endogenous default risk, for the government, for banks, for firms, and for households. It has rich interactions between the different default risks, and captures various “doom loops”: For example, higher default risk for firms leads to lower investment, which leads to lower output, which leads to higher default risk for the government. From a methodological viewpoint, it is an impressive achievement. Those who are religious about strict microfoundations may object to a number of shortcuts taken in formalizing the behavior of banks and the determination of the various spreads, but the shortcuts strike me as reasonable and a fully microbased treatment is probably beyond reach at this point.The authors, however, face a major specification issue: their model is not a model of a country with a Troika program. Much of what happened in Greece from 2010 on has been determined by the two programs, rather than by decisions of the Greek government or the Greek banks. The authors make the choice of ignoring this aspect. This may well be the right choice in showing what a model with default risk can do, but it creates problems of interpretation when applied to Greece, problems that I will return to below.They capture the stance of fiscal policy by a rule determining the deficit as a function of debt, of the cost of borrowing measured by the spread on Greek sovereign bonds, and of a fiscal shock. But, in fact, the stance of fiscal policy has been mostly determined by the amount of funding given by the Troika, and the interest rate at which the government has obtained this funding has been much lower than the rate on the secondary market for Greek government bonds. This makes the interpretation of “fiscal shocks,” estimated as residuals from a nonexistent rule, rather difficult.A related problem concerns banks. In the model, the rate at which banks can borrow depends on their default risk and on a funding shock (which the authors also call a sudden stop shock). The banks pass that cost on to their customers, so the rate at which banks can borrow determines the rate at which people and firms can borrow, adjusted for their own default risk. In the estimated model, much of the increase in the rate at which people and firms can borrow is interpreted as coming from an increase in the funding rate of banks. But, in fact, as we saw earlier, Greek banks have been able to borrow at low rates throughout, either from the ECB or from the Greek central bank. The implication is that the increase in spreads on lending to firms and households does not reflect a funding shock, but rather something else in the banking sector, probably the effects of losses on capital and in turn on credit supply. This makes the interpretation of the estimated funding shock difficult. It may capture the effect of a probability of euro exit, but in this case, it would affect other variables in the model, from the cost of borrowing by the government to investment.Turning to calibration and estimation, I have the same negative reaction I have to similar calibrations and estimations in other DSGEs. It is again an impressive technological tour de force. But, it is nearly impossible for the reader (at least for this reader) to get a good sense of the plausibility of the estimated/calibrated parameters, and, by implication, of the estimated shocks. Getting a sense of the various choices, be it which parameters are calibrated and which ones are estimated, which variables are chosen to be used for the estimation of shocks and which are left aside, and how robust the results are to assumptions, is difficult. I understand that it would take a much longer paper (or a very long appendix) to discuss and defend the various choices, but it makes it difficult to assess the results. Some of the choices strike me as debatable. To take a few examples: It cannot be right to use the same Calvo specification for wages in every country (or maybe for any country). The best way to find out what the fiscal multipliers were in Greece since 2007 cannot be to estimate the full DSGE model. Some implications of the calibration seem implausible. The elasticity of investment with respect to interest rates seems too large: A 60 basis point increase in the rate appears to decrease investment by 8% and output by 3%. This plays an important role in the results. I believe that general equilibrium Bayesian estimation just asks too much of the data, and is too much of a black box. From both a communication viewpoint and from a robustness viewpoint, I believe that much of the needed evidence must be collected through careful partial equilibrium, equation by equation, estimation, before we can run DSGEs with enough comfort. (I think it can be done. Indeed, an IV approach to estimation was followed by one of the authors [Martin and Philippon 2015] in a related paper.)Let me now go back to the three questions about Greece posed earlier. What does the model tell us?Take the role of fiscal policy, both in the boom and in the bust. Figure 18 presents the decomposition of movements in output as a result of the underlying shocks. And, on the face of it, it yields a surprising conclusion. While much of the pre-crisis increase in output is attributed to positive fiscal spending shocks, relatively little of the fall in output since then is attributed to negative fiscal shocks. Why is this? The authors explain it well. Shocks are defined as deviations of spending from the (postulated) fiscal rule. And given that the rule makes spending depend on the rate on sovereign bonds, it implies that, even in the absence of fiscal shocks, the large increase in spreads would have implied a large fiscal consolidation. The logic is fine, but the conclusion is potentially misleading. If we defined the fiscal spending shocks instead as the change in the cyclically adjusted primary surplus imposed by the Troika programs, they would account for much more of the decline in output. (One other aspect of the decomposition also puzzles me. The buildup in debt from 2010 to today is attributed nearly fully to positive spending shocks, which took place before the crisis. I find the long lags difficult to believe.)Take the role of other shocks. Particularly interesting is the role of markup shocks. As discussed earlier, one of the puzzling features of the adjustment has been the limited pass-through of wages to prices, slowing the competitiveness adjustment. Surprisingly (and with a slight tension between text and figure 18), markup shocks play a limited role in accounting for the decline in output. (The model allows for an effect of financial conditions on marginal cost through the use of working capital in production. Higher spreads imply higher costs, and thus an increase in prices relative to wages. This is an interesting angle, but will need to be documented at more directly). However, negative markup shocks, that is, incomplete pass-through of increases in wages into prices, play a substantial role in the pre-crisis buildup in output. This is a new angle in the discussion and worth exploring further.Finally, given where Greece was when the crisis started, how painful would the adjustment have been absent further shocks? I asked the authors to see what the model implied, by setting all the shocks equal to zero from 2010 on, so the dynamics from then on only depend on the state variables in 2009. They kindly did it, and the results are shown in the attached figure 1. The conclusion is that, despite the buildup of debt and the initial overvaluation, the contraction in output would have been substantially smaller. The mechanism behind the result, however, is suspicious. One would have expected that, in the absence of sovereign risk shocks and fiscal spending shocks the adjustment of government spending would be smaller, leading to a smaller output contraction. This, however, is not the main mechanism at play. Government spending without shocks is nearly the same as with shocks. The main difference is in the behavior of investment, which falls much less than in the presence of shocks. This in turn is due to turning off the funding cost shock, and the large elasticity of investment to the funding cost; as discussed earlier, I am skeptical about the interpretation of the funding cost shock, and the elasticity of investment, and thus skeptical about the conclusion.Fig. 1. Counterfactual simulation, no shocks after 2010Note: Eight series: GDP, Investment, Net Exports/GDP, Govt. Spending, Funding Cost, NPL, Govt. Yield, and my too me what I at the The model in this paper is not at the stage where it will about what behind the Greek But it has an extremely rich structure, which can be on and lead to a much more interesting discussion of what has happened in Greece in the last of and of the financial if see and the and the in the in Previous articleNext article by NBER by the National of by the National of All no articles this

This study aims to examine and analyze the effect of Profitability, Liquidity, Free cash flow, and firm size on Firm Value through Capital Structure as an intervening variable in mining companies listed on the Indonesia Stock Exchange. The population of this study is all mining companies listed on the Indonesia Stock Exchange for the period 2014-2020. The sample used in this study amounted to 30 companies. This type of research uses associative research methods. Data analysis used path analysis approach using SPSS program. The results showed that profitability had a positive and significant effect on firm value. Liquidity, free cash flow , firm size, and capital structure have a negative and insignificant effect on firm value. Profitability and liquidity have a negative and significant effect on capital structure. Free cash flow has a positive and insignificant effect on the capital structure. Firm size has a positive and significant effect on capital structure. Based on the results of the mediation test, it shows that the Capital Structure is not able to act as an intervening variable.