Popular in Professional

Architecture

Connecting Cities and Nature

University of Virginia Timothy Beatley

Human Rights Law

Human Rights and Corruption: Problems and Potential of Individualising a Systemic Problem

Max Planck Institute Anne Peters

Finance

Chinese Exchange Rate Policy: Lessons for Global Investors

University of California San Diego Michael Melvin

Law

A statistical approach to law school citation rankings

University of Virginia Joshua Fischman

Education

Firm Performance Pay as Insurance against Promotion Risk

Stockholm School of Economics Alvin Chen

Constitutional Law

What is constitutional ideology?

University of Oxford Nick Barber

The imprint of labor markets on entrepreneurial performance

View more insights in Professional - Business - Entrepreneurship and Innovation

View more figures from University of Calgary

View the page of Seok-Woo Kwon

Next in Business

Feature Misspecification in Sequential Learning Problems

Dongwook Shin | Hong Kong University of Science and Technology

The Allegory of the Favela: The Multifaceted Effects of Socioeconomic Mobility

Leandro S. Pongeluppe | University of Pennsylvania

Seok-Woo Kwon discusses the earnings of individual entrepreneurs from the beginning of their entrepreneurial careers, examining the effects of labor markets on their earnings trajectory.

Image courtesy of interviewee. July 31, 2024

Log-in or Sign-up to Faculti
Currently viewing this subject insight as a guest. You have insight(s) remaining for this month. Login to view 8000+ figures on the platform.

Generating Workspace...

Export as PDF

This video is a transcription of a discussion between a professor and an interviewer regarding a study on the impacts of labor markets on entrepreneurial performance. The professor explains that the research stemmed from questions posed by students during the 2008 economic recession about the feasibility of starting a business during such trying economic times.

The professor highlights findings from labor economics literature, illustrating that individuals who enter the job market in a challenging economy tend to face long-term earnings disadvantages compared to those who enter during favorable conditions. This video phenomenon, known as an "earnings gap," persists even after economic recovery and affects various groups, including PhD graduates.

The main aim of the professor's study is to explore whether similar long-term consequences apply to entrepreneurs who start businesses in a poor economy. The research looks at the imprinting hypothesis, suggesting that entrepreneurs who start businesses during challenging times may adopt lower-risk, lower-return strategies that influence their long-term performance.

The study uses the National Longitudinal Survey of Youth dataset, which tracks individuals over time, allowing for analysis of their earnings trajectories. Preliminary findings reveal that starting a business in a bad economy is correlated with decreased earnings, persisting for as long as ten years. Notably, a 1% increase in initial unemployment rates could lead to a 13% reduction in entrepreneurs' earnings.

The discussion also covers factors that might ameliorate these negative outcomes, such as relocating or shifting sectors, which can help entrepreneurs reset their trajectories. Ultimately, the research indicates that while starting a business in a bad economy poses greater risks, those who survive beyond five years can earn more than non-entrepreneurs in stable employment, suggesting that entrepreneurship can still pay off in the long run despite initial challenges. Future research areas were mentioned, but specific directions were not detailed in the excerpt.

Language:

Export as PDF

Export as PDF
Here are five key points derived from the video:

1. **Impact of Economic Conditions on Entrepreneurship**: The speaker discusses the effects of starting a business in a bad economy, specifically during the recession of 2008, highlighting that individuals entering the business world during challenging economic times may adopt more conservative, low-risk strategies, which can negatively impact their long-term earnings and business performance.

2. **Long-Term Earnings Consequences**: Research suggests that entrepreneurs who start in a bad economy face enduring gaps in earnings compared to those who start in a good economy, with a striking statistic indicating that a 1% increase in unemployment at the time of entry correlates to a 13% decrease in earnings over the following years.

3. **Imprinting Hypothesis**: The speaker references the imprinting hypothesis from sociology, which posits that experiences in formative years have long-lasting influences on individuals and organizations. This is applied to entrepreneurs, indicating that their initial experiences in a challenging economic environment might shape their future business decisions and strategies.

4. **Methodology and Dataset**: The study utilizes longitudinal data from the National Longitudinal Survey of Youth, enabling researchers to track participants' career trajectories from youth into their prime working years. This dataset allows for a comprehensive analysis of how initial economic conditions influence later earning patterns.

5. **Comparison to Non-Entrepreneurs**: Interestingly, despite the challenges of starting a business in a bad economy, entrepreneurs who manage to survive for more than five years may eventually earn more than their peers in salaried positions. This highlights the potential for entrepreneurship to be a beneficial long-term career path, even in adverse economic conditions, the entrepreneur can withstand the initial difficulties.

Export as PDF
Here are some key quotes from the video that summarize its main points and findings regarding entrepreneurship in a bad economy:

1. **Initial Doubt**:
- "I was getting a question from the students whether it is still good to start business in this kind of business environment. And I really didn't have a good answer for that."

2. **Long-Term Earnings Impact**:
- "What is surprising about the research is that even after the economy recovers... you still have... a big earnings gap between people who enter in a good job market and a bad job market."

3. **Historical Data**:
- "So our contribution is that instead of looking at this selection effect, we will need to look at the what we call treatment effect of labor, initial economy."

4. **Imprinting Hypothesis**:
- "If the entrepreneurs start business in a bad economy, they will probably adopt more low risk, low return kind of business strategy... that will have a long lasting influence on their performance in the long run."

5. **Data Sources**:
- "Fortunately, we are able to obtain a data set called the National Longitudinal Survey of Youth... it started in collecting data in 1979."

6. **Unemployment Rate Impact**:
- "One percent increase in unemployment at the initial entry point will lead to about 13% decrease in entrepreneurs' earnings."

7. **Comparative Advantage**:
- "Entrepreneurs starting in a bad economy will not do as well... compared to the entrepreneurs starting in a good economy."

8. **Long-Term Benefits of Survival**:
- "Even in a bad economy, entrepreneurship pays off in the long run compared to salaried employees if they survive five years."

These quotes encapsulate the central themes of the discussion, including the initial hesitations regarding starting a business in a challenging economy, the effects of economic conditions on entrepreneurial outcomes, and the long-term implications of those early decisions.

X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

00:00.245 --> 00:04.845
I was teaching, entrepreneurship class, to,

00:04.845 --> 00:09.005
and during the great recession of 2008,

00:09.325 --> 00:13.125
I was getting a question from the students whether,

00:13.345 --> 00:16.765
it is still good to start business in this kind of,

00:16.825 --> 00:18.125
business environment.

00:18.825 --> 00:23.605
Uh, and I really didn't have a good answer for that.

00:24.105 --> 00:27.565
Uh, so I did, I started to look at,

00:27.625 --> 00:30.765
in the literature, what kind of research has been done.

00:31.185 --> 00:34.765
Uh, and the closest thing that I could find,

00:34.825 --> 00:37.885
is from the, labor economics.

00:38.035 --> 00:41.885
Basically, they were studying, college graduates

00:42.485 --> 00:45.045
entering job market in a bad economy.

00:45.585 --> 00:50.245
Uh, and what they found, obviously, compared

00:50.265 --> 00:54.685
to the people who are entering into good job market,

00:55.345 --> 00:58.885
so your initial earnings are a little bit lower.

00:59.065 --> 01:01.365
That's kind of obvious that's to be expected.

01:01.865 --> 01:06.845
But what is surprising about, the research, is

01:06.915 --> 01:10.485
that, even after the economy recovers and

01:10.485 --> 01:14.885
after four, five years down the road, you still have,

01:14.985 --> 01:18.525
sort of the big, earnings gap between people

01:18.585 --> 01:21.245
who enter in a good job, good job market,

01:21.345 --> 01:22.685
and a bad job market.

01:23.225 --> 01:25.525
And that was pretty intriguing.

01:26.135 --> 01:28.845
Again, this is not entrepreneurship, but,

01:28.865 --> 01:31.285
but this is, people who are entering into labor market.

01:31.745 --> 01:33.685
And then there are also other studies

01:33.985 --> 01:36.325
who look at MBA students, for example,

01:36.745 --> 01:40.045
or people who are, entering,

01:40.145 --> 01:41.725
job market in a good economy.

01:42.055 --> 01:46.445
Again, good, MBA salaries,

01:46.785 --> 01:48.405
can accumulate over time.

01:48.865 --> 01:51.285
And if you look at, if you compare people

01:51.345 --> 01:55.325
who are entering good job market versus bad job market,

01:55.505 --> 01:59.285
the lifetime, income difference can be as large

01:59.305 --> 02:02.965
as 1 million to five, a million US dollars.

02:03.705 --> 02:06.285
So that was a pretty huge,

02:06.625 --> 02:11.045
and for finally, for the PhD,

02:11.465 --> 02:16.045
economist who entering the job market, again,

02:16.145 --> 02:19.525
the, the research suggests that there is an immediate hit.

02:19.745 --> 02:23.725
Uh, if you are entering job market in a, a bad market,

02:23.795 --> 02:27.485
then you're less likely to be hired by a prestige university

02:27.545 --> 02:30.805
and also, or you are less likely to get a,

02:30.925 --> 02:33.485
a tenure track jobs, more sort

02:33.485 --> 02:35.245
of the permanent track kind of jobs.

02:35.825 --> 02:39.685
And this effect continues up to about 12 years.

02:40.265 --> 02:42.925
So when you go back to the, people

02:43.185 --> 02:47.845
who started at the job, bad job market, you are,

02:47.935 --> 02:50.485
still finding that they are lagging behind.

02:50.945 --> 02:54.605
Uh, and what's most fascinating is also they are lagging

02:54.605 --> 02:58.205
behind, not just in the sort of the earnings, but also their

02:58.625 --> 02:59.625
Output quality.

02:59.825 --> 03:02.925
So they publish less number of papers,

03:03.385 --> 03:07.405
and also they publish, in, less,

03:08.245 --> 03:09.485
I guess they were not able

03:09.485 --> 03:11.725
to publish in a high quality journals.

03:12.145 --> 03:14.725
So all of this was, fascinating.

03:15.225 --> 03:19.085
Uh, but again, going back to the, my initial question.

03:19.345 --> 03:21.685
So what is the long-term consequence

03:21.865 --> 03:24.325
of starting a business in a bad economy?

03:24.825 --> 03:27.165
Uh, I didn't, have that answer.

03:27.385 --> 03:31.245
So, so leveraging on these kind of, labor market,

03:31.565 --> 03:33.165
research, I will, I wanted to sort

03:33.165 --> 03:35.005
of look at the similar question in

03:35.005 --> 03:36.485
the entrepreneurship context.

03:37.165 --> 03:40.925
I think the literature on macroeconomic condition

03:40.925 --> 03:44.405
and entrepreneurship, basically look at

03:44.555 --> 03:46.725
what we call selection effect.

03:47.185 --> 03:51.805
Uh, basically means that, whether good economy

03:52.065 --> 03:55.925
or bad economy encourages more entrepreneurship.

03:56.875 --> 04:00.855
So like most academic leaders, there are two,

04:00.855 --> 04:01.935
schools of thought.

04:02.395 --> 04:05.535
So, one school of thought says that, there is a,

04:05.895 --> 04:08.215
a recession push hypothesis.

04:08.635 --> 04:12.215
Uh, in other words, bad, economy

04:12.765 --> 04:15.775
will create more entrepreneurial entry

04:15.775 --> 04:19.015
because people cannot get a, a regular job,

04:19.115 --> 04:20.615
so they start their own business.

04:21.315 --> 04:24.655
And then the other, sort of perspective argues

04:24.655 --> 04:27.095
that prosperity pool hypothesis.

04:27.475 --> 04:30.975
So good job, good economy, lead

04:30.975 --> 04:33.575
to more entrepreneurial, entry.

04:34.065 --> 04:38.735
Again, the mix, the empirical evidence is mixed.

04:39.315 --> 04:43.655
Uh, and, the kind of, the literature here,

04:44.195 --> 04:47.295
was not yielding any new insight.

04:47.675 --> 04:51.655
So the, my, our contribution, is that instead

04:51.655 --> 04:54.775
of looking at this selection effect, we will need

04:54.775 --> 04:59.095
to look at the, what we call treatment effect of labor,

04:59.165 --> 05:00.615
initial, economy.

05:01.675 --> 05:04.735
So what's going to happen, if you

05:05.265 --> 05:09.815
start a business in a bad economy, will

05:09.885 --> 05:12.415
that effect will be short term

05:12.955 --> 05:15.855
or maybe, it could be also long term.

05:16.075 --> 05:20.455
So, so we draw on the imprinting hypothesis from,

05:20.835 --> 05:21.975
sociology.

05:22.105 --> 05:26.615
There is a great, sociology named the Stinchcomb,

05:26.675 --> 05:29.095
who published book in 1965,

05:29.355 --> 05:34.295
and argues that, just like young animals, who are,

05:34.635 --> 05:37.175
strongly influenced by their,

05:37.225 --> 05:40.455
early years experience, organizations

05:40.555 --> 05:44.815
and business can be, also strongly, influenced

05:44.915 --> 05:49.135
by the stamp of the environment in a formative period.

05:49.955 --> 05:52.615
Uh, so we suspect,

05:52.715 --> 05:54.215
or our intuition is

05:54.215 --> 05:58.925
that if the entrepreneurs start business in a bad economy,

05:59.625 --> 06:04.325
they will probably adopt more low risk, low return kind

06:04.325 --> 06:06.325
of business strategy,

06:06.585 --> 06:07.845
and that will going

06:07.845 --> 06:11.765
to have a long lasting influence on their,

06:11.955 --> 06:14.125
performance, in the long run.

06:14.625 --> 06:17.845
So there is a bit of, evidence for that.

06:18.185 --> 06:23.125
Uh, for example, prior research suggests that if,

06:23.715 --> 06:28.405
CEOs who experience recession as a manager, not as a CEO,

06:28.665 --> 06:32.325
but as a manager, if they experience recession,

06:32.435 --> 06:36.045
then when they become CEO, they spend,

06:36.115 --> 06:37.685
less in r and d.

06:38.185 --> 06:42.245
And also they are very concerned about cost effectiveness.

06:42.825 --> 06:44.485
So the earlier experience

06:44.505 --> 06:48.245
of managers can still influence their,

06:48.245 --> 06:52.245
current CEO job, I guess the,

06:52.365 --> 06:55.205
their strategy of managing their organization.

06:55.465 --> 06:58.805
So I think the same thing could be happening,

06:59.435 --> 07:01.365
with the entrepreneurs as well.

07:01.705 --> 07:06.445
So, so our hypothesis of this paper was that whether,

07:06.785 --> 07:08.965
the effect of labor market

07:09.105 --> 07:12.205
or the economy at entry will

07:12.795 --> 07:17.285
persist over entrepreneurs earning trajectory,

07:17.835 --> 07:18.845
over long time.

07:19.145 --> 07:22.885
So we just wanted, we wanted to test that, ideas

07:23.355 --> 07:24.365
with the dataset.

07:24.465 --> 07:27.165
In order to examine this hypothesis.

07:27.785 --> 07:30.725
We need a longitudinal data set.

07:31.185 --> 07:35.885
Uh, because we are interested in, trajectory

07:36.385 --> 07:41.045
of entrepreneurs earnings over the years, we need,

07:41.225 --> 07:43.605
we need to able to track their

07:44.325 --> 07:46.285
earnings history for some time.

07:46.745 --> 07:48.565
So, fortunately, we are able to

07:49.105 --> 07:52.565
obtain a data set called the National Longitudinal Survey

07:52.705 --> 07:57.605
of Youth, and it's a US data set.

07:57.745 --> 08:02.245
Uh, it's a national representative sample of about 12,000,

08:02.425 --> 08:03.645
individuals.

08:04.385 --> 08:08.605
Uh, and it started in collecting data,

08:08.865 --> 08:11.445
in 1979,

08:12.065 --> 08:15.805
and when the respond was about 14

08:16.185 --> 08:18.045
to 22 years old.

08:18.745 --> 08:22.885
Uh, and the last wave we have from this data set was

08:23.265 --> 08:24.405
2010,

08:24.915 --> 08:28.325
when the respondents were about 45

08:28.545 --> 08:29.925
to 53.

08:30.825 --> 08:32.325
So, the,

08:32.395 --> 08:36.045
this data set covers their prime working years.

08:36.785 --> 08:40.445
Uh, and another advantage of this data set is

08:40.445 --> 08:42.725
that we are able to track,

08:43.345 --> 08:47.605
the individual's career from the very, beginning.

08:47.865 --> 08:51.285
So, so we are able to create a, a career trajectory.

08:52.105 --> 08:54.725
And, with the, with this, with this

08:54.755 --> 08:59.725
Data set, we also combined, unemployment rate,

08:59.725 --> 09:02.165
information from the, US census.

09:02.865 --> 09:07.445
Uh, so we are able to look at the unemploy, the influence

09:07.505 --> 09:11.205
of unemployment rate in, the location

09:11.255 --> 09:13.325
where these individuals live,

09:13.585 --> 09:18.085
and then how does that, influence, their,

09:18.745 --> 09:20.285
earnings trajectory.

09:20.785 --> 09:24.445
Uh, and some of them are regular employees

09:24.585 --> 09:27.605
and some of them, starts their own business.

09:27.745 --> 09:32.725
So I, we are able to compare, their, entrepreneurial

09:33.765 --> 09:37.005
earnings trajectory, for some individuals.

09:37.065 --> 09:40.645
And we also all look at the sort, the wage,

09:41.165 --> 09:42.765
earnings trajectory for others.

09:42.875 --> 09:47.645
Something we need to make sure is that we are comparing,

09:48.105 --> 09:50.205
apples and apples,

09:50.345 --> 09:53.365
or we, we shouldn't be comparing apples and oranges.

09:54.065 --> 09:58.965
So when we are comparing, entrepreneurs who

09:59.675 --> 10:03.485
started in good economy versus bad economy,

10:03.985 --> 10:07.885
we wanna make sure that they are comparable while people

10:08.895 --> 10:11.605
turns out that they are not comparable.

10:11.945 --> 10:15.845
Uh, when I, when I look at entrepreneurs who started,

10:16.145 --> 10:20.525
in a bad economy, they tend to be younger.

10:21.155 --> 10:24.125
They tend to have a lower cognitive ability,

10:24.535 --> 10:27.685
lower intelligence, less education,

10:28.425 --> 10:31.965
and they have a, a high employment on

10:32.695 --> 10:34.605
insta insta instability.

10:35.145 --> 10:38.565
Uh, and also they had a lower wage,

10:38.565 --> 10:40.565
before they enter entrepreneurship,

10:40.705 --> 10:43.965
and they were mostly engaged in manual task.

10:45.105 --> 10:49.125
So, we wanted to first of all,

10:49.755 --> 10:52.205
control for this statistically

10:52.785 --> 10:57.005
and, be able to compare similar kinds

10:57.005 --> 11:01.325
of individuals entering in two different kind of,

11:02.005 --> 11:03.445
economic, situations.

11:04.065 --> 11:05.765
So we, we did that.

11:06.215 --> 11:11.205
After we have done that, we found that, the,

11:11.305 --> 11:15.605
initial, unemployment rate,

11:16.465 --> 11:21.245
at the time of entry has a long-term influence as long

11:21.305 --> 11:24.045
as 10 years after entry.

11:24.705 --> 11:28.805
So, for example, one, percent,

11:29.505 --> 11:34.135
increase in unemployment at the

11:34.135 --> 11:38.135
initial, entry point will lead to about

11:38.975 --> 11:42.295
13% decrease in,

11:42.885 --> 11:44.615
entrepreneurs earnings.

11:45.275 --> 11:49.335
Uh, so that was a pretty dramatic, finding,

11:49.875 --> 11:51.655
we found.

11:52.555 --> 11:55.685
So what are the, reasons

11:55.945 --> 11:58.085
or mechanisms behind it?

11:58.625 --> 12:03.565
Uh, our, speculation is that there is,

12:04.115 --> 12:09.005
some kind of task specific human capital,

12:09.095 --> 12:11.925
being developed by the entrepreneurs.

12:12.265 --> 12:15.685
So if I give, maybe,

12:17.005 --> 12:21.545
if I could give an example, instead of starting,

12:21.945 --> 12:25.345
restaurants, maybe entrepreneurs will go,

12:25.755 --> 12:26.945
start food trucks.

12:27.245 --> 12:32.105
If they are starting in a, a, a bad economy,

12:32.445 --> 12:36.065
and one, even after the economy improves,

12:36.065 --> 12:40.225
because they started at the, they were, being,

12:40.765 --> 12:45.345
so used to, they already invested in certain kind

12:45.345 --> 12:48.745
of skills they need, running a food truck,

12:48.895 --> 12:51.465
they are more likely to stay there,

12:51.725 --> 12:54.305
and then it'll have a long-term,

12:54.375 --> 12:57.985
influence on their earnings trajectory down the road.

13:00.025 --> 13:03.005
So, one may.

13:03.265 --> 13:06.685
So we also found that, if

13:07.515 --> 13:12.325
entrepreneurs, move away from the location

13:12.455 --> 13:15.365
where they start their initial business,

13:16.105 --> 13:21.045
or they start different kind of business, then they,

13:21.515 --> 13:23.805
they were able to reset the clock.

13:24.225 --> 13:28.805
And, the initial influence of bad,

13:29.145 --> 13:33.645
economy has, a lot less influence on their,

13:33.985 --> 13:35.245
later incomes.

13:35.385 --> 13:39.005
So there were a bit of a moderation effect.

13:39.225 --> 13:43.525
One of the interesting policy question is that,

13:44.385 --> 13:48.685
is encouraging entrepreneurship by government officials

13:49.305 --> 13:54.125
in a bad economy really a, a good, policy.

13:54.985 --> 13:59.725
Uh, so I think the, the answer to this,

14:00.005 --> 14:01.525
question is a little bit nuanced.

14:01.905 --> 14:06.645
Uh, if you are comparing, entrepreneurs,

14:06.785 --> 14:10.165
who are starting in a good economy versus bad economy,

14:10.815 --> 14:15.285
turns out that our research suggests that, may

14:15.925 --> 14:18.645
compared to the entrepreneurs starting in a good economy,

14:19.335 --> 14:20.405
maybe,

14:20.405 --> 14:24.925
entrepreneurs starting in a bad economy will not do as well.

14:25.785 --> 14:29.245
On the other hand, if we compare,

14:29.435 --> 14:33.445
entrepreneurs starting a bad economy with the,

14:33.905 --> 14:37.085
non entrepreneurs, employees who just,

14:37.085 --> 14:40.645
who never try entrepreneurship, it turns out

14:40.795 --> 14:45.645
that even if entrepreneur who starts in a bad economy, if,

14:46.065 --> 14:49.125
they can survive for more than five years,

14:49.555 --> 14:50.605
that is big if,

14:50.605 --> 14:54.605
Because a lot of, new business fail.

14:55.025 --> 14:58.085
But if they can survive for more than five years,

14:58.665 --> 15:02.845
it turns out that they earn more than comparable,

15:02.945 --> 15:04.445
salary employees.

15:05.105 --> 15:10.045
So even in a bad economy, entrepreneurship pay off,

15:10.145 --> 15:13.285
in the long run compared to the,

15:13.965 --> 15:17.245
salaried employees if they survive five years.

15:17.585 --> 15:20.645
But if they don't, then I think that's a different question.

"Navigating Entrepreneurship During Economic Turmoil: Insights from Labor Market Research"

00:00:00 - I was teaching, entrepreneurship class, to, and during the great recession of 2008, I was getting a question from the students whether, it is still good to start business in this kind of, business environment. and I really didn't have a good answer for that. so I did, I started to look at, in the literature, what kind of research has been done. and the closest thing that I could find, is from the, labor economics. Basically, they were studying, college graduates
00:00:45 - and what they found, obviously, compared to the people who are entering into good job market, so your initial earnings are a little bit lower. That's kind of obvious that's to be expected. But what is surprising about, the research, is that, even after the economy recovers and after four, five years down the road, you still have, sort of the big, earnings gap between people who enter in a good job, good job market, and a bad job market.
00:01:26 - Again, this is not entrepreneurship, but, but this is, people who are entering into labor market. And then there are also other studies who look at MBA students, for example, or people who are, entering, job market in a good economy. Again, good, MBA salaries, can accumulate over time. And if you look at, if you compare people who are entering good job market versus bad job market, the lifetime, income difference can be as large as 1 million to five, a million US dollars.
00:02:06 - and for finally, for the PhD, economist who entering the job market, again, the, the research suggests that there is an immediate hit. if you are entering job market in a, a bad market, then you're less likely to be hired by a prestige university and also, or you are less likely to get a, a tenure track jobs, more sort of the permanent track kind of jobs. And this effect continues up to about 12 years. So when you go back to the, people who started at the job, bad job market, you are,
00:02:50 - and what's most fascinating is also they are lagging behind, not just in the sort of the earnings, but also their Output quality. So they publish less number of papers, and also they publish, in, less, I guess they were not able to publish in a high quality journals. So all of this was, fascinating. but again, going back to the, my initial question. So what is the long-term consequence of starting a business in a bad economy? I didn't, have that answer. So, so leveraging on these kind of, labor market,
00:03:33 - of look at the similar question in the entrepreneurship context. I think the literature on macroeconomic condition and entrepreneurship, basically look at what we call selection effect. basically means that, whether good economy or bad economy encourages more entrepreneurship. So like most academic leaders, there are two, schools of thought. So, one school of thought says that, there is a, a recession push hypothesis. in other words, bad, economy

"Analyzing the Impact of Economic Conditions on Entrepreneurial Success: Insights and Hypotheses"

00:04:15 - because people cannot get a, a regular job, so they start their own business. And then the other, sort of perspective argues that prosperity pool hypothesis. So good job, good economy, lead to more entrepreneurial, entry. Again, the mix, the empirical evidence is mixed. and, the kind of, the literature here, was not yielding any new insight. So the, my, our contribution, is that instead of looking at this selection effect, we will need
00:04:59 - initial, economy. So what's going to happen, if you start a business in a bad economy, will that effect will be short term or maybe, it could be also long term. So, so we draw on the imprinting hypothesis from, sociology. There is a great, sociology named the Stinchcomb, who published book in 1965, and argues that, just like young animals, who are, strongly influenced by their,
00:05:40 - and business can be, also strongly, influenced by the stamp of the environment in a formative period. so we suspect, or our intuition is that if the entrepreneurs start business in a bad economy, they will probably adopt more low risk, low return kind of business strategy, and that will going to have a long lasting influence on their, performance, in the long run. So there is a bit of, evidence for that.
00:06:23 - CEOs who experience recession as a manager, not as a CEO, but as a manager, if they experience recession, then when they become CEO, they spend, less in r and d. And also they are very concerned about cost effectiveness. So the earlier experience of managers can still influence their, current CEO job, I guess the, their strategy of managing their organization. So I think the same thing could be happening,
00:07:01 - So, so our hypothesis of this paper was that whether, the effect of labor market or the economy at entry will persist over entrepreneurs earning trajectory, over long time. So we just wanted, we wanted to test that, ideas with the dataset. In order to examine this hypothesis. We need a longitudinal data set. because we are interested in, trajectory of entrepreneurs earnings over the years, we need,
00:07:44 - earnings history for some time. So, fortunately, we are able to obtain a data set called the National Longitudinal Survey of Youth, and it's a US data set. it's a national representative sample of about 12,000, individuals. and it started in collecting data, in 1979, and when the respond was about 14 to 22 years old. and the last wave we have from this data set was

"Analyzing Career Trajectories: The Impact of Economic Conditions on Entrepreneurial and Wage Earnings"

00:08:24 - when the respondents were about 45 to 53. So, the, this data set covers their prime working years. and another advantage of this data set is that we are able to track, the individual's career from the very, beginning. So, so we are able to create a, a career trajectory. And, with the, with this, with this Data set, we also combined, unemployment rate, information from the, US census. so we are able to look at the unemploy, the influence
00:09:11 - where these individuals live, and then how does that, influence, their, earnings trajectory. and some of them are regular employees and some of them, starts their own business. So I, we are able to compare, their, entrepreneurial earnings trajectory, for some individuals. And we also all look at the sort, the wage, earnings trajectory for others. Something we need to make sure is that we are comparing,
00:09:50 - or we, we shouldn't be comparing apples and oranges. So when we are comparing, entrepreneurs who started in good economy versus bad economy, we wanna make sure that they are comparable while people turns out that they are not comparable. when I, when I look at entrepreneurs who started, in a bad economy, they tend to be younger. They tend to have a lower cognitive ability, lower intelligence, less education,
00:10:32 - insta insta instability. and also they had a lower wage, before they enter entrepreneurship, and they were mostly engaged in manual task. So, we wanted to first of all, control for this statistically and, be able to compare similar kinds of individuals entering in two different kind of, economic, situations. So we, we did that. After we have done that, we found that, the,
00:11:16 - at the time of entry has a long-term influence as long as 10 years after entry. So, for example, one, percent, increase in unemployment at the initial, entry point will lead to about 13% decrease in, entrepreneurs earnings. so that was a pretty dramatic, finding, we found.
00:11:55 - or mechanisms behind it? our, speculation is that there is, some kind of task specific human capital, being developed by the entrepreneurs. So if I give, maybe, if I could give an example, instead of starting, restaurants, maybe entrepreneurs will go, start food trucks. If they are starting in a, a, a bad economy, and one, even after the economy improves,

"Long-Term Earnings Trajectories: The Impact of Economic Conditions on Entrepreneurs"

00:12:40 - so used to, they already invested in certain kind of skills they need, running a food truck, they are more likely to stay there, and then it'll have a long-term, influence on their earnings trajectory down the road. So, one may. So we also found that, if entrepreneurs, move away from the location where they start their initial business,
00:13:21 - they were able to reset the clock. And, the initial influence of bad, economy has, a lot less influence on their, later incomes. So there were a bit of a moderation effect. One of the interesting policy question is that, is encouraging entrepreneurship by government officials in a bad economy really a, a good, policy. so I think the, the answer to this,
00:14:01 - if you are comparing, entrepreneurs, who are starting in a good economy versus bad economy, turns out that our research suggests that, may compared to the entrepreneurs starting in a good economy, maybe, entrepreneurs starting in a bad economy will not do as well. On the other hand, if we compare, entrepreneurs starting a bad economy with the, non entrepreneurs, employees who just, who never try entrepreneurship, it turns out
00:15:17 - they can survive for more than five years, that is big if, Because a lot of, new business fail. But if they can survive for more than five years, it turns out that they earn more than comparable, salary employees. So even in a bad economy, entrepreneurship pay off, in the long run compared to the, salaried employees if they survive five years. But if they don't, then I think that's a different question.

Faculti AI can make mistakes

Research

Policy

Analysis