Contribution: I use unique transaction-level data to document the effects of introducing digital money, a monetary expansion, and a currency crisis on transaction activity in a barter community in Toronto.
Context: Bunz is a community started by millennials in Toronto in 2013 to exchange personal possessions (e.g., used clothing, accessories, furniture, and plants). They arrange to trade in person through a mobile app platform with ~10K daily active users
The community has one rule: No cash!
As a result, Bunz users often used beer, store gift cards, and transit tokens to complete transactions. The problem of double coincidence was real! 👇
To reduce trade frictions, the platform introduced a digital token named BTZ in April 2018.
The token could be transferred among users, or redeemed for retail goods at designated local stores at a fixed exchange rate. It was not otherwise convertible.
(think: pegged currency with capital controls)
At first, transaction volume didn't change much.
Then, in September 2018, the platform increased token issuance through helicopter drops to users in an attempt to drive user engagement. As a result, the token supply quintupled.
This large monetary expansion did not create inflation, as measured using store gift cards posted on the app with a BTZ price.
But monetary expansion increased in-person transactions by almost 70%, as measured by ratings that users provide for each other after trade completion.
This increase in transactions was persistent and was not due to new users or a new supply of items. Rather, it coincided with increased token transfers on the app.
Takeaway: monetary expansion helped users overcome the problem of double coincidence.
A year later, however, token redemptions were partially halted due to financial strain.
This triggered a currency crisis.
Users immediately rushed to coffee shops and restaurants to redeem tokens for food and drink.
Many users stopped accepting the token.
The share of new items posted on the platform with a BTZ price plummeted.
Transaction volume fell by 25%.
In the paper, I interpret these events through the lens of a search model of money where the token value is fixed (Kiyotaki-Wright 1993).
Takeaway: When barter is difficult and the token value is fixed, money is both non-neutral and essential.
Our contribution: While prior work uses *firm-level* variation to measure the effect of outsourcing on wages, we use *market-level* variation from Brazil's 1993 outsourcing legalization to assess the aggregate effects of outsourcing on wages, employment, and welfare.
Our focus: Security guards, who experienced the largest rise in outsourcing following legalization
Data: RAIS matched employer-employee data with industry and occupation codes to identify outsourcing