Economics Letters 203 (2021) 109869

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Economics Letters
journal homepage: www.elsevier.com/locate/ecolet

Productivity of firms using relief policies during the COVID-19 crisis

∗
Masayuki Morikawa
Hitotsubashi University, 2-1 Naka, Kunitachi, Tokyo 186-8603, Japan
Research Institute of Economy, Trade and Industry (RIETI), 1-3-1 Kasumigaseki, Chiyoda-ku, Tokyo 100-8901, Japan

article info a b s t r a c t

Article history: This study, based on an original survey of Japanese firms, analyzes the productivity of firms that used
Received 9 March 2021 relief policy measures during the COVID-19 pandemic. The productivity of firms using these relief
Received in revised form 13 April 2021 measures was lower than that of non-user firms prior to the pandemic, suggesting that inefficient firms
Accepted 15 April 2021
have been affected seriously. The result cautions against the excessive and prolonged relief policies.
Available online 20 April 2021
© 2021 Elsevier B.V. All rights reserved.
JEL classification:
D24
H25
L25

Keywords:
COVID-19
Relief policies
Productivity
Cleansing effect
Reallocation effect

1. Introduction the subsidization rate is set to 100% of the maximum. Even for
large firms, the maximum subsidy rate is raised to 75%.1
The COVID-19 pandemic has had a serious impact on the If a firm that could have survived goes bankrupt or goes out
of business voluntarily because of a temporary shock, the sunk
global economy. Many countries have adopted emergency mea-
investments will be lost. For this reason, policies that mitigate
sures to mitigate the impact of the pandemic on business activity;
the impacts of temporary shocks can be justified. However, it is
Japan is no exception. To relieve firms that are affected seriously, necessary to acknowledge the risk that such policies may weaken
the Japanese government enacted various emergency measures, the resource reallocation mechanism and have a negative impact
such as financial assistance from governmental financial agencies, on medium- to long-term economic growth potential.
the Subsidy Program for Sustaining Businesses (hereafter ‘‘sus- The cleansing effect of recessions, that is, the increased pro-
tainability subsidy’’), and the Employment Adjustment Assistance ductivity that arises from the exit of unproductive firms from the
Subsidy (hereafter ‘‘employment subsidy’’). market during recessions, has been pointed out in the literature
Financial assistance programs offering low- or zero-interest (e.g., Caballero and Hammour, 1994). Generally, industry-level or
loans target small- and medium-sized firms experiencing economy-wide productivity growth can be broken down into the
pandemic-related sales declines. The sustainability subsidy began within-effect and the reallocation effect. Empirical studies found
in May 2020, delivering a maximum of two million yen to small- stronger reallocation effects during recessions (e.g., Baily et al.,
and medium-sized firms with a drop in sales of more than 2001; Foster et al., 2001; Disney et al., 2003; Carreira and Teixeira,
2008).
50%. The employment subsidy is a measure that supports firms’
However, recent studies indicate weak reallocation effects af-
efforts to maintain employment and has been in place since
ter the Great Recession. Foster et al. (2016), for example, found
long before the COVID-19 crisis. However, the subsidization rate that the intensity and productivity enhancing effects of reallo-
was raised significantly in April 2020. Specifically, for small- and cation were small in the Great Recession. Using a sample of
medium-sized firms with sales that declined by more than 5%, manufacturing firms in European countries, Landini (2020) indi-
cated that the market selection mechanism based on productivity
∗ Corresponding author at: Hitotsubashi University, 2-1 Naka, Kunitachi, differentials was weak during the Great Recession.
Tokyo 186-8603, Japan.
E-mail addresses: morikawa@ier.hit-u.ac.jp, 1 The maximum amount of daily benefits per employee is also raised to
morikawa-masayuki@rieti.go.jp, BXZ00354@nifty.ne.jp. 15,000 yen.

https://doi.org/10.1016/j.econlet.2021.109869
0165-1765/© 2021 Elsevier B.V. All rights reserved.
M. Morikawa Economics Letters 203 (2021) 109869

The negative impacts of surviving inefficient firms on the 3. Results

overall economy are referred to as a problem of ‘‘Zombie’’ firms
(e.g., Caballero et al., 2008; Kwon et al., 2015; Imai, 2016). Mal- The percentages of firms used relief policies are (1) financial
function of the financial market – banks continuing to keep credit assistance (25.0%), (2) the sustainability subsidy (19.3%), and (2)
flowing to otherwise insolvent borrowers – is often cited as a the employment subsidy (44.1%).3 By firm size, the percentages
primary cause of weak reallocation mechanisms during the long of policy users are higher in small- and medium-sized firms
stagnation in Japan. McGowan et al. (2018) applied the method- (i.e., firms capitalized at 100 million yen or less) than in large
ology of Caballero et al. (2008) to nine OECD countries, indicating firms across all policies. As many policies are designed to place
that the prevalence of Zombie firms has risen since the mid- importance on small- and medium-sized firms, this is a natural
2000s, and the increasing survival of these unproductive firms result.
congests markets and constrains the growth of more productive Columns (1) and (2) of Table 1 presents the mean productivity
firms. of firms that used relief policies relative to those that did not use
The lesson learned from these studies is that firm relief mea- policies with t-test results. For all three policies, the productivity
sures during the recent COVID-19 crisis might serve to suppress of firms using relief policies is lower and the differences are
the function of cleansing or reallocation effects and exert a neg- statistically significant at the 1% level, irrespective of the produc-
ative impact on the medium- to long-term productivity of the tivity measures. Quantitatively, the TFP of firms using financial
economy. Barrero et al. (2020) analyzed the reallocation of em- assistance, sustainability subsidy, and employment subsidy are
ployment and sales under the COVID-19 pandemic in the U.S. 18.9, 11.9, and 12.4 log points lower, respectively. In short, the
and cautioned against the excessive use of policies that inhibit productivity of firms that used relief policies was lower than the
resource reallocation. non-users, even before the onset of the COVID-19 crisis. Columns
Against the background, this study analyzes the productiv- (3) and (4) indicate the difference in mean firm size. The size of
ity of firms that have used relief policies during the COVID-19 firms using relief policies is generally smaller, with an exception
pandemic. The result indicates that the productivity of the firms of the number of employees for employment subsidy.
that benefited from these relief measures tended to be lower Table 2 reports the OLS regression coefficients for policy users,
than non-user firms prior to the COVID-19 crisis. The policy wherein the firm size and three-digit industry are controlled.
implication is that relief measures under the recent COVID-19
The coefficients for the use of relief policies are all negative and
crisis should be temporary and such policies should be modified
statistically significant at the 1% level. In the case of the LP, the
to enable the smooth reallocation of resources.
absolute sizes of the coefficients are slightly smaller than the
2. Survey design and method of analysis figures presented in Table 1, but the sizes are almost unchanged
in the case of the TFP. Overall, these results indicate that various
The data used in this study are from the ‘‘Survey of Corpo- support measures may have the aspect of bailing out not only
rate Management and Economic Policy’’ (SCMEP). The SCMEP is firms with suddenly deteriorating business performance due to
an original firm survey conducted by the Research Institute of the COVID-19 pandemic but also firms that had low-productivity
Economy, Trade and Industry from late August to early September prior to the pandemic.
2020. The survey questionnaire was sent to 2498 Japanese firms
that had responded to the previous SCMEP in early 2019. As 4. Conclusion
the sample of the SCMEP was selected from the Basic Survey of
Japanese Business Structure and Activities (BSJBSA, conducted by Using data from a survey of Japanese firms, this study in-
the Ministry of Economy, Trade and Industry), the firms chosen dicates that the productivity of firms that use relief policies is
to take part in the SCMEP had at least 50 employees, capital of at lower before the onset of the COVID-19 pandemic than non-user
least 30 million yen, and belonged to manufacturing, wholesale, firms. Temporary relief policies to support affected firms can be
retail, and service industries. The number of firms that responded justified, but the results of this study caution against the poten-
to the current SCMEP is 1579 (a response rate of about 63%). tial negative side effects of excessive or overly prolonged relief
The question on the use of relief policy measures was: ‘‘Which policies from the viewpoint of long-term productivity of the econ-
of the following policies that have been introduced due to COVID- omy. As it will take some time to end the COVID-19 pandemic
19 has your firm used or would like to use in the future?’’ and the industrial structure after the crisis will undoubtedly be
The specific policies included were (1) financial assistance from different from that before the pandemic, a gradual downsizing
governmental financial agencies, (2) the sustainability subsidy, of the relief policies and restructuring policy measures toward
and (2) the employment subsidy. supporting growing sectors are desirable approaches.
The firm characteristics available from the SCMEP are limited, While this study presents unique evidence on Japanese firms’
but more information can be obtained by linking the data with use of relief policies during the COVID-19 pandemic, we observe
the BSJBSA. In this study, we calculate labor productivity (LP) the productivity distribution of firms only before the COVID-19
and total factor productivity (TFP) for fiscal year 2018 (i.e., April crisis. Evaluating the ex post performance of firms that used relief
2018–March 2019) from the BSJBSA and analyze the relationship policies and the productivity dynamics of the economy is left for
between the use of relief policies and productivity prior to the future research.
COVID-19 crisis. In addition, the three-digit industry classification
is taken from the BSJBSA.2 Acknowledgments
We calculate firms’ LP as the firms’ value-added divided by the
total hours worked and express the value in logarithmic form. We I thank the editor, Joseph E. Harrington, and an anonymous
calculate TFP as a cost-share-based index number using value- referee for their helpful comments. I am grateful to the Ministry
added, the book value of capital, total hours, and the cost shares of Economy, Trade and Industry for providing microdata from
of capital and labor. The index number is the relative productivity the BSJBSA used in this study. This research is supported by the
level compared with a hypothetical representative firm of the JSPS Grants-in-Aid for Scientific Research (16H06322, 18H00858,
same three-digit industry. Using the data set, we compare the 20H00071, 21H00720).
productivity of policy users and non-users before the onset of the
COVID-19 crisis. 3 The percentages of firms that answered ‘‘want to use’’ in the future are (1)
financial assistance (14.2%), (2) the sustainability subsidy (13.3%), and (3) the
2 Three-digit industry classification is the finest breakdown in the BSJBSA. employment subsidy (18.3%).

2
M. Morikawa Economics Letters 203 (2021) 109869

Table 1
Mean productivity and size of firms using relief policies.
(1) LP (2) TFP (3) Employment (4) Capital
Financial assistance −0.2703 *** −0.1888 *** −0.2146 *** −0.6828 ***
Sustainability subsidy −0.2055 *** −0.1185 *** −0.0761 −0.3226 ***
Employment subsidy −0.2015 *** −0.1239 *** 0.0754 * −0.1921 ***

Notes: The figures indicate the difference with firms not using relief policies. *** p < 0.01 (t-test). LP, TFP, employment, and capital
expressed in logarithm are for fiscal year 2018.

Table 2
Regression results on the productivity of firms using relief policies.
(1) (2) (3) (4) (5) (6)
Financial assistance Sustainability subsidy Employment subsidy
LP TFP LP TFP LP TFP
Policy dummy −0.1949 *** −0.1853 *** −0.1159 *** −0.1188 *** −0.1603 *** −0.1467 ***
(0.0249) (0.0246) (0.0340) (0.0333) (0.0241) (0.0240)
Firm size Yes Yes Yes Yes Yes Yes
Industry dummies Yes Yes Yes Yes Yes Yes
Adjusted R2 0.3407 0.0622 0.3205 0.0375 0.3360 0.0541
Nobs. 1465 1457 1465 1457 1465 1457

Notes: OLS estimations with robust standard errors in parentheses. *** p < 0.01. Both the LP and TFP expressed in logarithm are
for fiscal year 2018. Firm size is the number of employees (expressed in logarithm).

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