Supply Chain Network and Macroeconomic Expectations of Firms

Last registered on October 19, 2024

Pre-Trial

Trial Information

General Information

Title
Supply Chain Network and Macroeconomic Expectations of Firms
RCT ID
AEARCTR-0014480
Initial registration date
October 18, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
October 19, 2024, 11:01 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Region

Primary Investigator

Affiliation
New York University (AD)

Other Primary Investigator(s)

PI Affiliation
Federal Reserve Bank of Cleveland
PI Affiliation
Auckland University of Technology New Zealand
PI Affiliation
New York University Abu Dhabi
PI Affiliation
Federal Reserve Bank of Cleveland

Additional Trial Information

Status
On going
Start date
2024-07-08
End date
2025-04-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this paper, we explore the role of supply chain networks in shaping macroeconomic expectations. We address this question using a theoretical model that integrates firm networks and the transmission of macroeconomic shocks, combined with a randomized control trial of 1074 firm-firm pairs in New Zealand. By introducing exogenous variation in expectation through an information treatment that provides the 2025 GDP forecast (mean or variance) to treated firms, we analyze both the direct effects on firms receiving this information and the network effect on connected firms that did not directly receive information. One of the key contributions of this project is to explore how communication and other transmission channels such as observing price changes along the supply chain -- which may differ between upstream and downstream firm connections -- influence firms' expectation formation. In macroeconomics, expectation formation is a critical issue, and supply chains present a potentially underexplored mechanism. The insights from our findings will have important implications for how central banks communicate information to firms.
External Link(s)

Registration Citation

Citation
Hajdini, Ina et al. 2024. "Supply Chain Network and Macroeconomic Expectations of Firms." AEA RCT Registry. October 19. https://doi.org/10.1257/rct.14480-1.0
Experimental Details

Interventions

Intervention(s)
Our intervention has two treatment arms and one control arm.
1—Treatment 1 (Mean Treatment): The information provided in this arm concerns the first moment of the GDP forecast, i.e., the first moment of future economic growth.
2—Treatment 2 (Uncertainty Treatment): The information provided in this arm concerns the second moment of the GDP forecast, i.e., the second moment of future economic growth.
3- Control: No information is provided in this arm.
Intervention Start Date
2024-07-08
Intervention End Date
2024-09-30

Primary Outcomes

Primary Outcomes (end points)
1- Expectations. Macroeconomic expectations come from the baseline surveys (priors) and endline surveys (posteriors).

2-Economic Decisions. The second outcome examines firm's economic decisions (relating to the prices, employment, investment and wages).
Primary Outcomes (explanation)

The baseline survey collects the priors using the following questions:
1- What do you think will be the annual growth rate of real GDP in New Zealand in twelve months? Please provide an answer in percentage terms.
Answer: …………… \% per year

Could you provide us with an approximate range of what you think annualized real GDP growth in New Zealand will be over the next 12 months?
Answer: Real GDP growth over the next 12 months will be between ....... % per year (lowest forecast) and ...... % per year (highest forecast)

This question is directed exclusively to firms that received the treatment.
Please let me know what you perceive as the most pessimistic, the most likely, and most optimistic real GDP growth rate for New Zealand over the next 12 months. What do you think the lowest annualized real GDP growth rate might be for this time period, what do you think the most likely might be, and what do you think the highest might be? (please provide an answer as % per year).
Lowest real GDP growth rate: ……….. \% per year
Most likely GDP growth rate: ……….. \% per year
Highest real GDP growth rate: ……….. \% per year

The endline survey collects this information using the following question:
Please let me know what you perceive as the most pessimistic, the most likely, and most optimistic real GDP growth rate for New Zealand over the next 12 months. What do you think the lowest annualized real GDP growth rate might be for this time period, what do you think the most likely might be, and what do you think the highest might be? (please provide an answer as % per year).
Lowest real GDP growth rate: ……….. \% per year
Most likely GDP growth rate: ……….. \% per year
Highest real GDP growth rate: ……….. \% per year



The baseline survey collects the predictions of how the firm plans to change the prices over the next three months (prior to the information provided about the GDP forecast).

Over the next 3 months, by how much (in \% changes relative to current level) do you expect to change:
a) The price of your main product: ……………. \%
b) Investment in capital goods: ……………. \%
c) Employment at your firm: ……………. \%
d) Average wages: ……………. \%

The endline surveys ask the respondent the actual actions taken by the firm using the following question:

Over the last 3 months, by how much (in \% changes) did you change:
a. The price of your main product: ……………. \%\\
b. Investment in capital goods: ……………. \% \\
c. Employment at your firm: ……………. \% \\
d. Average wages: ……………. \%

Secondary Outcomes

Secondary Outcomes (end points)
1- Supply chain Dependent Expectation. We include the reasons behind the manager's responses on endline expectations to be related or unrelated to supply chain considerations.

2- Communication. The endline survey includes questions to quantify the frequency of communication for different topics between firms.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Using our firm-firm pairs, we randomly assigned the sample into three groups. The first group receives information about the first moment of GDP forecast (average GDP in Year 2025). We call this Treatment 1. In contrast, the second group receives information about the second moment of GDP forecast (uncertainty around GDP forecast for Year 2025). We call this Treatment 2. The last group receives no information and this is referred as the control group. Within each treated group, we further randomized whether the firm receives direct (main firm) or indirect information (linked firm). For the later group, we call those firms as untargetted treated firms because of their proximity to firms that receive direct information. By doing this, we are able to create 4 sub-groups for the treated sample: (1) Treatment 1 given to customer firms; (2) Treatment 1 given to supplier firms; (3) Treatment 2 given to customer firms; (4) Treatment 2 given to supplier firms.

We conduct the study in two waves in NZ with firms. The first is a baseline survey, during which the treated firms receive the information at the end. We then return to these firms after three months, allowing sufficient time for the information to disseminate.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by computer
Randomization Unit
Firm-Firm Pair
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Around 1000 Firm-Firm Pairs in Wave 1 (baseline)
Around 500 Firm-Firm Pairs in Wave 2 (endline) [due to expected attrition]
Sample size: planned number of observations
Around 2000 firms (suppliers + customers)
Sample size (or number of clusters) by treatment arms
Around 150 firm-firm pairs in Treatment 1 (where the customer is the main firm)
Around 150 firm-firm pairs in Treatment 1 (where the supplier is the main firm)
Around 150 firm-firm pairs in Treatment 2 (where the customer is the main firm)
Around 150 firm-firm pairs in Treatment 2 (where the supplier is the main firm)
300 - 400 firm-firm pairs in control.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
With the sample size of 150 (N1=75 treated and N2=75 control pairs), significance (alpha) equal to 5% and power (1-kappa) equal to 80%, the minimum detectable effect (MDE) is 0.46 SD. When we vary the sample size to 200, MDE=0.398 SD.
IRB

Institutional Review Boards (IRBs)

IRB Name
Auckland University of Technology Ethics Committee
IRB Approval Date
2024-10-03
IRB Approval Number
24/306
IRB Name
Aotearoa Research Ethics Committee, New Zealand
IRB Approval Date
2024-07-08
IRB Approval Number
AREC 24_20
IRB Name
New York University Abu Dhabi
IRB Approval Date
2024-07-30
IRB Approval Number
HRPP-2024-110