Have you wondered why the dates for EB2 India and EB3 India for Green Card are not moving and number of Green Card issued for EB2 India came from 23,000 to 3,000 in 3 years?
U.S. Immigration law allows foreign nationals to obtain Green Card (aka Permenant Residency in the USA) through Employment. There are three different Categories within Employment Based Green Card – EB1, EB2, EB3.
What about EB4 and EB5?
EB4 is for Religious Workers and EB5 is for Immigration through Investment (1 Million Dollars or $500,000 in certain areas).
There’s a set limit on how many Green Cards can be issued per year per country per preference category through Employment Based.
By the end of this article, you will have a clear understanding of how EB Spillover Rules work.
- Green Cards Quota Per Year via Employment = 140,000
If you are new to Green Card Process and don’t have a good understanding about the steps involved, read this U.S. Permanent Residency Green Card Process and Steps.
Here’s Annual Limits for Employment Based Green Card for FY 2018 from the Dept of State.
Each Country has a Cap of 7% Per category
- EB1, EB2 and EB3 = 7% of 40,040 = 2,803
- EB4 and EB5 = 7% of 9,940 = 696
If you look at I-485 Inventory data, there are four countries (India, China, Mexico and Philippines) that are typically impacted by backlogs (more applicants than available Green Cards Cap per country). Since, there’s not enough applicants from other counties, we have another Category of Country – Rest of the World (ROW).
When there’s unused Green Cards from other Categories, they began to move Up, Down and Sideways as underlined in the above picture – “Fall-Up” and “Fall-Down” and let me add one more term “Fall-Side“.
Now you have an idea about how Employment Based (EB) Green Card Category Spill Over Works. Let’s apply this theory with Real Data for FY 2017 Green Allocations by Country and Category.
- Every few months, USCIS publishes I-485 Inventory Data
- Every month Department of State publishes Visa Bulletin
With this knowledge about Spill Over, I-485 Inventory Data and Visa Bulletin, we have to answer the following questions:
- How to estimate the Priority Date movement from coming months?
- How to estimate the Green Card Wait Times using I485 Inventory Data?
- Why EB2 India, EB3 India is moving slower and EB3 China is moving fast?
Before we can answer the above questions, you have to understand the Role of USCIS and the Department of State. You may have noticed the following from two data sets.
- I-485 is filed with USCIS (Falls under Department of Homeland Security)
- Visa Bulletin is announced by the Department of State
As per immigration law, the number of available visa quota is controlled by the Department of State. They would release the number of Visa to USCIS, who would then Adjust the Status of Applicants to Permanent Residency.
The Department of State can technically give all the available EB Visa on the First Day of Fiscal Year (Oct 1) or Release the visa numbers as requested by USCIS every month or every quarter.
The Department of State doesn’t know, how many Visa numbers would be requested by USCIS.
USCIS doesn’t know how many visas would be released by DOS.
To better control the demand, DOS introduced Final action Dates and Filing Dates for I-485 to figure out the Visa Demand. So, USCIS would know in advance how many applicants would file for I-485.
Due to years of wait, not everyone with approved I-140 would file for I-485.
If you don’t understand the logic at work here, don’t worry. Move on to the next stage to understand How the Spill Over for Employment Based Green Card works.
EB Green Card Spill Over
- Unused EB4 would spill over to EB1
- Unused EB5 would spill over to EB1
- Unused EB1 would spill over to EB2
- Unused EB2 would spill over to EB3
Let’s look at each category with available Cap per year.
Fall Up – EB4 and EB5 to EB1
As you look at the numbers below, here’s how I’m getting the Numbers:
- Total Available = Based on Table 1 Above (As per US Immigration Law)
- Total Issued = Based on Annual Report published by Department of State
- Spill Over and Left Over = Manual Math based above two reports
EB4 FY 2017 Numbers:
- Total Available EB4 = 9,940 (as per Law)
- Total Issued for EB4 = 8,997
- Left Over EB4 = 9,940 – 8,997 = 943 (This Spills Over to EB1)
So, EB4 had a maximum of 9,940 for FY 2017. But, only 8,997 was issued. S0, unused 943 visas from EB4 would spill over to EB1.
EB5 FY 2017 Numbers
- Total Available EB5 = 9,940
- Total Issued for EB5 = 10,090
- Left Over from EB5 = 0
EB1 FY 2017 Number
- Total Available EB1 = 40,040
- Total Available with Spill Over from EB5 = 40,040 + 943 = 40,983
- Total Issued for EB1 = 41,827
Don’t ask me why 41,827 Visas were issued for EB1. That’s what reported in the Department of State’s Immigration Visa Report.
- Quiz: What does this mean for EB2? How many visas is available in total for EB2 for FY 2017?
EB2 FY 2017 Numbers
How many visas came from EB1 to EB2? The answer is ZERO!
Now, you should be getting an idea about why EB2 Numbers are not moving to India!
- Total Available EB2 = 40,040
- Total Available with Spill Over from EB1 = 40,040 + 0 = 40,040
- Total Issued for EB2 = 39,961
- Unused EB2 = 40,040 – 39,961 = 79
Quiz: When there’s a backlog in EB2 for India and China, why did 79 go unused? Well, I don’t know the answer, but, I think, is because the Visa Demand and the numbers given by Department of State.
It’s time to introduce one more Statistics here for EB2 India.
- Total EB2 Visa Issued for India for FY 2017 = 2,879
Now, you must be wondering!
What? Out of 40,040 available for EB2, why did India get just 2,879.
Before looking at deeper data within EB2, let me finish the math for EB3 for FY 2017. Then we can take a deeper dive within EB2 and EB3 and how “Fall-Side” works within Each Employment Based Preference Category.
Can you guess the answers?
Why don’t you ask the same questions with your friends?
Check what do they have to say. Majority of Non-Immigrants know about never ending Green Card wait times. Numbers of years vary (from 10 to 70 years).
You can even search around on Google to find How EB Spill Over works. There’s no detailed analysis like this one.
Now, you have read the Spill over math for EB2, it should be pretty easy to guess for EB3. If you haven’t guessed the answers, here’s the questions again.
- How many Visa did EB3 India get from EB2 Spill Over?
- Can you guess how many EB3 Visa was issued in India for FY 2017?
For the first question, you should know the answer based on my explanation so far in this page. If not, you must read it again for EB4 to EB5 to EB1 to EB2.
For the second question, you should be following the Report from Department of State. But, it’s easy to guess based on the EB2 numbers (to some extent).
- EB2 to EB3 spill over for India = 0
- Total Issued to EB3 India = 6,608 (FY 2017)
EB3 FY 2017 Numbers:
- Total Available EB3 = 40,040
- Total Available with Spill Over from EB2 = 40,040 + 0 = 40,040
- Total Issued for EB3 India = 6,608
- Total Issued for EB3 China = 2,348
- Total Issued for EB3 South Korea = 3,290
- Total Issued for EB3 Philippines = 6,492
- Total Issued for EB3 Overall = 34,938
Again, I don’t know only 34,938 was issued when available, numbers is 40,040 for FY 2017.
How did EB3 India get 6,608, when EB2 India got just 2,879 for FY 2017?
Simple Math at work here: Spilover from Rest of the World (ROW).
EB2, EB3 Spill Over: Deep Dive
- EB4 unused => EB1
- EB5 unused => EB1
- EB1 unused => EB1 Most Retrogressed countries => EB2 ROW
- EB2 ROW unused => EB2 Most retrogressed countries => EB3 worldwide
- EB3 ROW unused => EB3 retrogressed countries
So, how does this math within EB2 Work?
Total Available per country (lets take two countries)
- India – 2,803
- China – 2,803
Total Available for EB-2 for All Counties
- Total Available EB2 = 40,040
- Total Issued to India = 2,879 (as per report for FY 2017)
Let’s look at why EB2 India only 2,879.
Within EB2, allocated visas are split into the following buckets (as per I-485 Inventory Data):
- EB2 India
- EB2 China
- EB2 Mexico
- EB2 Philippines
- EB2 ROW (Rest of the World)
The most retrogressed country is India.
- Total Available for India in EB2 = 2,801
- Total Issued for EB2 India = 2,879
- Total Spill Over from EB2 ROW to EB2 India = 2,879 – 2,803 = 76
Yup. You read it right. Just 76 visa came from EB2 ROW.
Now, let’s look at the numbers for EB-2 India since 2018. Thanks to my friend who’s been keeping track of these EB-2 India numbers for these years.
- FY 2017 – 2,879
- FY 2016 – 3,930
- FY 2015 – 7,235
- FY 2014 – 23,527
- FY 2013 – 17,193
- FY 2012 – 19,726
- FY 2011 – 23,997
- FY 2010 – 19,961
- FY 2009 – 10,106
- FY 2008 – 14,806
As per this figure, the number of EB2 Visa issued for Indian Nationals came down drastically from FY 2014. Why did the numbers dry up?
There’s no spill over from EB1 to EB2 ROW and EB2 ROW to EB2 India.
Your next question should be based on the I-485 Inventory Data.
If 2879 Visa was issued, I should have received my Green card as per I485 Inventory Data. Why my priority dates are not moving?
EB3 to EB2 Porting
Another reason – There’s EB3 to EB2 porting.
Green Card applicants in EB3, would have gained enough experience and become eligible for EB2. Porting to EB2 would increase the wait times of EB2 applicants.
Ok. I hope I was able to articulate how to understand the Spill Over for Employment Based Green Cards.
Your next question – How do I calculate the Wait Times for my Green Card?
Above Math should have given you an estimate of how long it would take to get your Green Card if you apply for Green Card today.
If you want more insights, I have news for you. Check the following empty cells in the image below. I will analyze the data to get further insights.
EB Green Card Series of Articles
- How Long Does it Take to Get Green Card in the USA for Eb1, EB2, and EB3
- Green Card Steps for EB2 and EB3 Explained
- Green Card Visa Numbers availability for E1, EB2, and EB3
- US Green Card Waiting Time Based on Pending Applications
- Immigration Path: Steps for an F1 Visa to Become U.S. Citizenship
- How EB Green Card Spill Over between EB1, EB2, EB3, EB4 and EB5 works (this article)