| Field | Before | After |
|---|---|---|
| Field Trial Status | Before in_development | After on_going |
| Field Abstract | Before We present the motivation, design and analysis plan for the SEWA Wage Insurance Experiment (SWIE). The SWIE is a randomized controlled trial examining the impacts of providing so-called “hospi-cash" insurance that provides a per-diem indemnity payment while a beneficiary is hospitalized. We brand this a wage insurance product given SEWA' motivation for offering it, though it covers non-medical costs of hospitalization other than lost wages. The SWIE offers roughly 200 villages simultaneous access to two wage insurance plans, one with higher coverage and a higher price and one with lower coverage and lower price. The SWIE randomizes the prices to which villages are offered access to these two plans. The SWIE has two methodological innovations. First, it identifies bounds on demand using the approach in Tebaldi et al. (2018). Second, we develop an approach to choose prices so as to minimize the width of these bounds. The SWIE examines impacts on hospi-cash insurance uptake, health insurance uptake, hospi-cash insurance claims, and health care utilization. It also estimates adverse selection into and moral hazard from wage insurance. | After We present the motivation, design and analysis plan for the SEWA Wage Insurance Experiment (SWIE). The SWIE is a randomized controlled trial examining the demand for and impacts of providing so-called "hospi-cash'' insurance that provides a per-diem indemnity payment while a beneficiary is hospitalized. We brand this a wage insurance product because SEWA intends it to cover lost wages due to hospitalization, even though it can cover other costs and consequences of hospitalization as money is fungible. The SWIE offers roughly 200 villages access to two hospi-cash policies. The SWIE randomizes the prices to which villages are offered access to these two plans. The SWIE has two methodological innovations. First, it identifies sharp non-parametric bounds on demand using the approach in Tebaldi et al. (2019). Second, we develop a new approach to experimental design in order to choose prices so as to minimize the width of these non-parametric bounds. The SWIE also contributes to our understanding of the value of indemnity health insurance policies. The SWIE examines impacts of prices on hospi-cash insurance and health care insurance uptake and the impact of prices and uptake of hospi-cash on hospi-cash insurance claims and health care utilization. The evidence on uptake also estimates demand for indemnity insurance. The SWIE also estimates adverse selection into this wage insurance. Finally, the experiment also examine whether the hospi-cash insurance product improves risk-sharing within treatment villages. |
| Field Trial Start Date | Before June 26, 2019 | After March 01, 2022 |
| Field Trial End Date | Before March 31, 2021 | After April 30, 2024 |
| Field Last Published | Before July 02, 2019 01:43 PM | After July 15, 2022 12:04 PM |
| Field Intervention Start Date | Before September 11, 2019 | After July 25, 2022 |
| Field Intervention End Date | Before May 31, 2020 | After April 30, 2024 |
| Field Primary Outcomes (End Points) | Before 1. Uptake of each of the 2 selected hospi-cash products 2. Uptake of SEWA’s health insurance product and savings product 3. Days of hospitalization, by each member adult member and by any minor members of the household. In addition, the number of days reimbursed by health insurance. | After 1. Uptake of each of the 2 selected hospi-cash products 2. Uptake of health insurance products 3. Days of hospitalization, by each member adult member and by any minor members of the household. 4. Days of hospital treatment reimbursed under the hospi-cash policies |
| Field Experimental Design (Public) | Before This study will include two pilot surveys, a baseline survey, and an end line survey approximately one year after the end of the baseline. We will be running this experiment in 219 villages in Ahmedabad and Gandhinagar, two districts in the Indian state of Gujarat, which have 35,329 current and former SEWA members. In both pilots, we conduct surveys in three representative villages in Ahmedabad and two representative villages in Gandhinagar. Within each village, we select 50 representative households, yielding a total of 250 households in the first pilot and 250 households in the second pilot. Villages selected for the pilots are excluded from the main study. During the first pilot, we implement a willingness-to-pay exercise in five villages in Ahmedabad and Gandhinagar to determine which two products yield the most consumer surplus. We vary the products along two dimensions: indemnity rates (i.e., amount of money paid out when a claim is made) and coverage (i.e., number of people in a household covered). Within each village, we randomly assign 25 households to the insurance product that varies along the indemnity rate dimension, but is fixed along the coverage dimension, and 25 to the insurance product that varies along the coverage dimension, but is fixed along the indemnity rate dimension. We then choose the two products with the greatest consumer surplus. Approximately two weeks after the first pilot ends, the second pilot will begin. During the second pilot, we conduct another willingness-to-pay exercise focused on the two products selected in the first pilot. This pilot is conducted on survey respondents in a different set of five villages in Ahmedabad and Gandhinagar to determine optimal prices for the two products we've selected after the first pilot. After the pilots, we randomly assign the remaining 209 villages to one of the two possible prices for each of the two products offered. Again, within each village, we select 50 representative households, yielding a total of 10,450 households total. SEWA representatives will offer the two hospi-cash policies selected in pilot 1 to households in each village at the prices assigned to that village. SEWA will also continue to offer it's standard suite of non-hospi-cash policies to SEWA households. This hospi-cash marketing push will last 6 to 9 months. At the beginning of the marketing push we will conduct a baseline survey of sample households. After the marketing push, we will gather data from SEWA on which households purchased a hospi-cash policy and which one they purchased. We will also obtain from SEWA claims data for one year for for all sample households that enroll in a hospi-cash plan . Approximately one year after the end of the baseline, we will conduct an end line. We will estimate the causal impact of price on uptake of hospi-cash policies using an ITT design. We will back out bounds on the demand function using Tebaldi et al. (2018). We will examine the impact of enrollment in wage insurance on the uptake of SEWA's health insurance product, utilization of hospital care, employment, and household financial planning using randomized prices as an instrument in a TOT design. This design will also enable us to estimate adverse selection into and moral hazard from wage insurance. | After This study will include three pilot surveys, a baseline survey, and an endline survey approximately 18 months after the end of the baseline. The village and household samples for this study were assembled in two steps. First, we selected 214 villages in Ahmedabad and Gandhinagar districts in Gujarat state. Of these 214 villages, 5 were assigned to a pilot 1 that we used to determine which two hospi-cash policies we would study, 9 were assigned to the pilots 2 and 3 that we used to determine the price conditions for the experiment in the main study. The remaining 200 villages were used for the main study. Our inclusion criteria for households in the 3 pilot studies and the main study was that households have at least one SEWA member currently living there. (For example, the adult children of a SEWA member who no longer lives with them were ineligible to participate in the study.) While this criteria affects external validity, it provides a cohesive sample that already trusted SEWA and its financial services arm, VimoSEWA, and is thus likely to be cooperative with our study. There were no exclusion criteria for pilot 1. For pilots 2 and 3 and the main study, however, we excluded members that were subscribed to VimoSEWA's existing hospi-cash policy. We excluded these members because a member who already has a hospi-cash policy is unlikely to purchase a second policy. Moreover, we are interested in demand for hospi-cash amongst those who do not already have it. We also excluded members below the age of 18 and above the age of 54 from pilots 2 and 3 and the main study, as the hospi-cash policy is not available to individuals outside this age band. After the pilots, each of the 200 villages in the main study were randomly assigned villages to one of the four possible price-pairs for the two products offered. SEWA will also continue to offer it's standard suite of non-hospi-cash policies to SEWA households. In advance of the start of marketing, we will conduct a baseline survey of sample households. After marketing, we will gather data from SEWA on which households purchased a hospi-cash policy and which one they purchased. We will also obtain SEWA claims data for all sample households that enroll in a hospi-cash plan. Approximately 18 months after the end of the baseline, we will conduct an endline. |
| Field Randomization Unit | Before The unit of of randomization is a village. Each of the 209 villages are randomly assigned to a price 2-tuple for each of the 2 chosen products. 1. Villages are first sorted into 2-tuples based on the similarity of certain village-level features 2. In each 2-tuple, villages are randomly assigned (without replacement) to each of the 4 possible price combinations for the two wage insurance policies. All 209 villages are offered SEWA’s standard health insurance product at the SEWA-set premium. | After The unit of of randomization is a village. Each of the 200 villages are randomly assigned to a price 2-tuple for each of the 2 chosen products. 1. Villages are first sorted into 2-tuples based on the similarity of certain village-level features 2. In each 2-tuple, villages are randomly assigned (without replacement) to each of the 4 possible price combinations for the two wage insurance policies. All 200 villages are offered SEWA’s standard health insurance product at the SEWA-set premium. |
| Field Planned Number of Clusters | Before 209 villages | After 200 villages |
| Field Planned Number of Observations | Before 10,450 SEWA members | After 10,000 SEWA members |
| Field Sample size (or number of clusters) by treatment arms | Before 5,225 households randomized into each product's treatment arm | After 50 villages |
| Field Keyword(s) | Before Health | After Health |
| Field Public analysis plan | Before No | After Yes |
| Field Secondary Outcomes (End Points) | Before 1. Number of days of work in last month and average daily wage on days worked 2. Asset index 3. Savings 4. Monthly consumption budget (net of medical expenses) | After 1. Uptake of other insurance and/or financial products 2. Number of days of work in last month and average daily wage on days worked 3. Monthly income 4. Asset index 5. Savings 6. Monthly consumption expenditure (net of medical expenses) 7. Measures of within village consumption inequality (e.g. variance of log consumption for households in a village) 8. Monthly medical expenditures 9. Battery of health and wellness measures |
| Field Building on Existing Work | Before | After No |
| Field | Before | After |
|---|---|---|
| Field Document | Before |
After
SWIE___PAP___v_2022.pdf
MD5:
0dffe5d8bc2f8c0f945fc2f5b3d020de
SHA1:
7d5ea42e7ddfcbce1be5edcb83d8b1ad38ae94d6
|
| Field Title | Before | After SWIE - PAP - v.2022 |
| Field | Before | After |
|---|---|---|
| Field Affiliation | Before University of Chicago | After Columbia University |