Contract Parties & Project Scope

Field Details
Client Confidential Client
Project Scope Comprehensive analysis of incentive contract cash grants distribution
Data Source Puerto Rico Government Portal - Quarterly Cash Grants Report
Analysis Period FY 2017 - August 2025 (8+ years of data)
Deliverable Executive-ready analytical report with data quality assessment

Executive Summary

This report summarizes Puerto Rico Department of Economic Development quarterly cash-grant disclosures from fiscal year 2017 through August 2025 for 1,735 incentive contracts after PDF extraction and harmonization. Annual approved totals were limited through about 2019, then rose sharply from 2020 and peaked in 2023 and 2024, while the disbursed share within each contract year falls for the most recent cohorts, so a large and rising fraction of headline totals is approved-but-not-yet-paid capital rather than cash already disbursed. Contract-level disbursement ratios are concentrated near 0% and 100% (mean about 40%, median about 25%), with on the order of seven hundred contracts still at 0% disbursement, which flags backlog and timing risk when reading obligation totals. Choropleth funding bands and the ranked-municipality view both show heavy concentration of approved dollars in major coastal metros, notably San Juan and Aguadilla at the top of the list, while interior municipalities and smaller islands sit in lower funding tiers; disbursement efficiency relative to approvals varies widely across those municipalities (some smaller approvals disburse a high fraction; several large approvals show very low paid-to-date shares). The largest single-contract approved amounts skew toward pharmaceutical, medical device, and biotechnology manufacturing, with one Invest Puerto Rico related award as the dominant dollar outlier and cancellation uncommon among the top-ranked awards. Cumulative accounting by incentive category is dominated by machinery and equipment investment, with material balances in other reported categories, job creation/retention, and infrastructure investment, and comparatively small cumulative totals for specialized lines such as technology transfer and targeted SME programs, patterns that align with capital-equipment-heavy incentive use. Interpretation should stay tied to the methodology section on extraction, harmonization, and field definitions that affect counts, timing, and status labels.

Executive Summary Statistics

Methodology

Data Acquisition and Initial Processing

The primary data source for this analysis consists of quarterly cash grant reports published by the Puerto Rico Department of Economic Development, spanning fiscal years 2017 through August 2025. These reports were originally published as multi-page PDF documents containing tabular data on incentive contract distributions across municipalities and recipient organizations. Ozcorp Scientific LLC employed automated extraction algorithms to convert the PDF-formatted tables into machine-readable formats, initially producing comma-separated value files for downstream analytical processing. This extraction methodology was necessary due to the absence of structured data exports from the government portal.

Data Harmonization and Quality Control

Following initial data extraction, Ozcorp Scientific LLC implemented a systematic data harmonization protocol to address inconsistencies inherent in the manual data entry from the agency, as well as any errors stemming from the automated PDF extraction processes. The harmonization procedure involved standardizing date formats across temporal entries, normalizing currency field representations, and implementing text standardization algorithms to resolve variations in entity naming conventions. Quality control measures included identification and correction of optical character recognition artifacts, detection of duplicate entries resulting from typos, and validation of data completeness across all temporal periods. Statistical validation frameworks were applied to assess data integrity, with particular attention to identifying anomalous values that could indicate extraction or transcription errors requiring manual verification.

Note: The complete data aggregation, cleaning, and deduplication process is documented in the companion notebook 00_data_aggregation.Rmd. This analysis notebook imports the final clean dataset produced by that aggregation pipeline to ensure data integrity and eliminate double-counting issues that could arise from overlapping records between administrative periods.

Statistical Analysis Framework

The analytical approach employed descriptive statistical methods to characterize grant distribution patterns across temporal, geographic, and sectoral dimensions. Temporal analysis examined year-over-year trends in grant allocation volumes and identified potential seasonal or cyclical patterns in funding distributions. Geographic analysis focused on municipal-level grant concentrations, employing aggregation methods to identify regional patterns in economic development incentive targeting. Sectoral analysis examined grant distributions across recipient categories and organizational types, with particular attention to concentration patterns among high-volume recipients. Data quality metrics were continuously monitored throughout the analytical process to quantify the extent of harmonization requirements and assess the reliability of derived insights.

Visualization and Reporting Methodology

Visualization strategies were designed to communicate analytical findings through multiple complementary graphical representations, including temporal trend analyses, geographic distribution summaries, and recipient concentration studies. Each visualization employed consistent scaling methodologies to enable cross-temporal and cross-sectoral comparisons, with particular attention to maintaining visual clarity when representing large dynamic ranges in grant amounts. The reporting framework integrated quantitative findings with qualitative assessments of data quality limitations, providing context for interpretation of results within the constraints imposed by the original data extraction methodology. Statistical summaries were presented using standardized formatting to facilitate executive-level interpretation while maintaining scientific rigor in the presentation of uncertainty estimates and confidence intervals where applicable.

Data Import

## Clean dataset dimensions: 1735 34
## Total grant amount: $702,336,012
## Observed calendar years (min-max): 2016 to 2025
## Unique companies: 1256
## Unique municipalities: 78
## Unique grant categories (base): 12
## 
## Data Quality Check:
## Records from Previous Administration Only: 76
## Records from Current Administration Only: 643
## Records from Both Administrations: 1016
## Records with grant amount changes: 4
## Records with status changes: 70

Administration Change Analysis

Data Source Harmonization Strategy

The analysis incorporates data from two distinct administrative periods, requiring a specialized harmonization approach to track changes between administrations. This methodology enables identification of policy shifts, data quality improvements, and administrative differences that may impact contract reporting and execution.

## 
## === ADMINISTRATION DATA SOURCE SUMMARY ===
## # A tibble: 3 × 6
##   data_source    record_count total_grant_amount total_cancelled total_disbursed
##   <chr>                 <int>              <dbl>           <dbl>           <dbl>
## 1 Both Administ…         1016         452109899.       32451342.      135298808.
## 2 Current Admin…          643         233785707.       10840004.       52498789.
## 3 Previous Admi…           76          16440407.        8067500         5858852.
## # ℹ 1 more variable: avg_grant_amount <dbl>
## 
## === CHANGES IN OVERLAPPING CONTRACTS ===
## # A tibble: 1 × 14
##   total_contracts contracts_with_grant_changes contracts_with_status_changes
##             <int>                        <int>                         <int>
## 1            1016                            4                            70
## # ℹ 11 more variables: contracts_with_cancelled_changes <int>,
## #   contracts_with_disbursed_changes <int>, total_grant_increase <dbl>,
## #   total_grant_decrease <dbl>, net_grant_change <dbl>,
## #   total_cancelled_increase <dbl>, total_cancelled_decrease <dbl>,
## #   net_cancelled_change <dbl>, total_disbursed_increase <dbl>,
## #   total_disbursed_decrease <dbl>, net_disbursed_change <dbl>
## 
## === PREVIOUS ADMINISTRATION TOTALS (for overlapping contracts) ===
## # A tibble: 1 × 4
##   total_grant_prev total_cancelled_prev total_disbursed_prev avg_grant_prev
##              <dbl>                <dbl>                <dbl>          <dbl>
## 1       453287399.             2588926.            94992939.        446149.
## 
## === CURRENT ADMINISTRATION TOTALS (for overlapping contracts) ===
## # A tibble: 1 × 4
##   total_grant_curr total_cancelled_curr total_disbursed_curr avg_grant_curr
##              <dbl>                <dbl>                <dbl>          <dbl>
## 1       452109899.            32451342.           135298808.        444990.

Cash Grant Data Harmonization

## === CASH GRANT CATEGORY SUMMARY ===
## Total unique categories: 12
## Categories with single contract: 3
## Categories with >10 contracts: 6
## [1] "All Cash Grant Categories:"
## # A tibble: 12 × 6
##    grant_category_base           count total_amount avg_amount min_year max_year
##    <chr>                         <int>        <dbl>      <dbl>    <dbl>    <dbl>
##  1 Inversión en Maquinaria/Equi…   300   399347268.   1331158.     2019     2025
##  2 Otros                           822   129829168.    157943.     2019     2025
##  3 Creación/Retención de Empleos   313    90509631     289168.     2018     2025
##  4 Inversión en Infraestructura     50    68483530.   1369671.     2019     2025
##  5 Transferencia de Tecnología       7     5860000     837143.     2023     2024
##  6 PYMES Innovadoras                23     2490000     108261.     2021     2025
##  7 Servicios Profesionales           5     1978967     395793.     2024     2025
##  8 Industrias Creativas            206     1968239.      9555.     2022     2025
##  9 Renta Incentivada                 1     1483614    1483614      2016     2016
## 10 Apoyo Empresarial                 6      325000      54167.     2024     2024
## 11 Sin Categoría                     1       50595      50595      2023     2023
## 12 Ayuda PYMES Huracán Fiona         1       10000      10000      2022     2022
## 
## === POTENTIAL DATA QUALITY ISSUES ===
## 
## === CATEGORIES WITH SINGLE CONTRACTS (Potential Errors) ===
## # A tibble: 3 × 6
##   grant_category_base       count total_amount avg_amount min_year max_year
##   <chr>                     <int>        <dbl>      <dbl>    <dbl>    <dbl>
## 1 Renta Incentivada             1      1483614    1483614     2016     2016
## 2 Sin Categoría                 1        50595      50595     2023     2023
## 3 Ayuda PYMES Huracán Fiona     1        10000      10000     2022     2022

Plot 1: Aggregate Cash Grant Amount Per Year

## [1] "Yearly Grant Totals with Disbursement Information:"
## # A tibble: 9 × 6
##   `Contract Year` `Total Approved (M)` `Total Disbursed (M)` `Undisbursed (M)`
##             <dbl>                <dbl>                 <dbl>             <dbl>
## 1            2016                1.48                  1.43             0.0547
## 2            2018                0.528                 0.390            0.138 
## 3            2019               31.0                  16.7             14.3   
## 4            2020              124.                   59.2             64.8   
## 5            2021               69.8                  33.7             36.1   
## 6            2022              111.                   31.6             79.9   
## 7            2023              144.                   33.4            111.    
## 8            2024              153.                   15.6            137.    
## 9            2025               67.1                   1.55            65.5   
## # ℹ 2 more variables: `Disbursement Rate (%)` <dbl>, `Contract Count` <int>

Plot 2: Cash Grant Distribution by Municipality (Puerto Rico Map)

## === FUNDING RANGE CALCULATION ===
## Min amount: $ 0.00 M
## Q1 (25th percentile): $ 0.3 M
## Q2 (50th percentile/median): $ 1.5 M
## Q3 (75th percentile): $ 8.6 M
## Q90 (90th percentile): $ 22.2 M
## Max amount: $ 128.2 M
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## [1] "Funding Range Distribution Summary:"
## # A tibble: 5 × 4
##   `Funding Range`           Municipalities `Total Amount` `Average Amount`
##   <fct>                              <int> <chr>          <chr>           
## 1 Very High (>$22.2M)                    8 $430.2M        $53.8M          
## 2 High ($8.6M-$22.2M)                   12 $173.0M        $14.4M          
## 3 Medium-High ($1.5M-$8.6M)             19 $ 82.0M        $ 4.3M          
## 4 Medium-Low ($0.3M-$1.5M)              19 $ 14.4M        $ 0.8M          
## 5 Low ($0.00M-$0.3M)                    20 $  2.7M        $ 0.1M
## [1] "Top 10 Municipalities by Total Funding:"
## # A tibble: 10 × 4
##    Municipality `Funding Range`     `Total Amount` Contracts
##    <chr>        <fct>               <chr>              <int>
##  1 SAN JUAN     Very High (>$22.2M) $128.2M              317
##  2 AGUADILLA    Very High (>$22.2M) $107.8M               54
##  3 GUAYAMA      Very High (>$22.2M) $ 41.6M               15
##  4 JUANA DÍAZ   Very High (>$22.2M) $ 36.9M               17
##  5 YAUCO        Very High (>$22.2M) $ 35.8M               15
##  6 ARECIBO      Very High (>$22.2M) $ 31.1M               41
##  7 CIDRA        Very High (>$22.2M) $ 26.6M               13
##  8 AÑASCO       Very High (>$22.2M) $ 22.3M               13
##  9 SAN LORENZO  High ($8.6M-$22.2M) $ 22.1M               15
## 10 MAYAGÜEZ     High ($8.6M-$22.2M) $ 21.2M               57

Plot 3: Cash Grant Amount by Contract Number (Colored by Status)

## [1] "Top 20 Contracts Overall - Status Summary:"
## # A tibble: 3 × 4
##   contract_or_cancelled       contract_count total_amount avg_amount
##   <chr>                                <int>        <dbl>      <dbl>
## 1 Contract                                18    251021846  13945658.
## 2 Cancelled (Balance pending)              1     50000000  50000000 
## 3 Cancelled                                1      7000000   7000000
## [1] "Top 20 Contracts Overall by Grant Amount:"
## # A tibble: 20 × 6
##    `Contract Number` `Grant Amount` Status         Recipient Municipality Sector
##    <chr>                      <dbl> <chr>          <chr>     <chr>        <chr> 
##  1 2020-001077             50000000 Cancelled (Ba… INVEST P… SAN JUAN     PROFE…
##  2 2023-001914             28000000 Contract       SARTORIU… YAUCO        MANUF…
##  3 2024-000563             25000000 Contract       COOPERVI… JUANA DÍAZ   HEALT…
##  4 2021-000178             22450000 Contract       PF CONSU… GUAYAMA      MANUF…
##  5 2022-000216             22000000 Contract       COPAN IN… AGUADILLA    MANUF…
##  6 2025-000745             21500000 Contract       CARIBBEA… CIDRA        MANUF…
##  7 2025-000443             18000000 Contract       ETHICON … SAN LORENZO  MANUF…
##  8 2024-000542             14310000 Contract       ABBVIE B… BARCELONETA  MANUF…
##  9 2025-000019             13424000 Contract       AMO PUER… AÑASCO       HEALT…
## 10 2022-000432-A           13000000 Contract       BIOSOMIL… AGUADILLA    MANUF…
## 11 2025-000221             10500000 Contract       THERMO K… ARECIBO      CONST…
## 12 2023-002139             10000000 Contract       BAXTER H… AIBONITO     MANUF…
## 13 2020-000420              8760000 Contract       BOEHRING… SAN JUAN     MANUF…
## 14 2023-002370              8000000 Contract       CERVECER… MAYAGÜEZ     MANUF…
## 15 2024-000170              7707846 Contract       COOPERVI… JUANA DÍAZ   HEALT…
## 16 2022-000151              7500000 Contract       CytoInmu… TOA BAJA     MANUF…
## 17 2023-000004              7270000 Contract       GUIDANT … DORADO       MANUF…
## 18 2021-000010-A            7000000 Cancelled      BECTON D… JUNCOS       HEALT…
## 19 2019-000389              6800000 Contract       FENWAL I… MAYAGÜEZ     MANUF…
## 20 2025-000052              6800000 Contract       AbbVie B… MANATÍ       HEALT…

## [1] "Top 10 Contracts per Sector - Status Summary:"
## # A tibble: 35 × 5
##    SECTOR         contract_or_cancelled   contract_count total_amount avg_amount
##    <chr>          <chr>                            <int>        <dbl>      <dbl>
##  1 MANUFACTURING  Contract                            10    166020000  16602000 
##  2 HEALTHCARE     Contract                             9     73306846   8145205.
##  3 PROFESSIONAL   Cancelled (Balance pen…              1     50000000  50000000 
##  4 CONSTRUCTION   Contract                            10     34226900   3422690 
##  5 PROFESSIONAL   Contract                             8     14729703   1841213.
##  6 INFORMATION    Cancelled                            7      9730000   1390000 
##  7 HEALTHCARE     Cancelled                            1      7000000   7000000 
##  8 OTHER_SERVICES Contract                            10      6629450    662945 
##  9 AGRICULTURE    Contract                             9      6378196    708688.
## 10 ADMINISTRATIVE Contract                             7      3700185    528598.
## # ℹ 25 more rows
## [1] "Top Contracts by Grant Amount (Top 10 per Sector):"
## # A tibble: 167 × 6
##    `Contract Number` `Grant Amount` Status    Recipient      Municipality Sector
##    <chr>                      <dbl> <chr>     <chr>          <chr>        <chr> 
##  1 2025-000736               465000 Contract  AC CULINARY G… BAYAMÓN      ACCOM…
##  2 2020-000167                56000 Cancelled MARVEL INTERN… GUAYNABO     ACCOM…
##  3 2023-002446                50000 Contract  ACTA LLC / YI… SAN GERMÁN   ACCOM…
##  4 2023-002258                50000 Contract  FILOMENA CARN… SAN JUAN     ACCOM…
##  5 2023-002397                50000 Contract  FNJCC CORPORA… PONCE        ACCOM…
##  6 2023-002393                50000 Contract  FRESCURA, LLC  BAYAMÓN      ACCOM…
##  7 2023-002441                50000 Contract  HEIDI L. IRIZ… ADJUNTAS     ACCOM…
##  8 2023-002315                50000 Contract  JAEO CORPORAT… GURABO       ACCOM…
##  9 2023-002256                50000 Contract  JOSE A. MONTA… BARCELONETA  ACCOM…
## 10 2023-002401                50000 Contract  OMAR SOTO MEN… MOCA         ACCOM…
## # ℹ 157 more rows

Plot 4: Cumulative Cash Grant Amount Per Year by Grant Category

## # A tibble: 12 × 3
##    grant_category_base            total_amount years_active
##    <chr>                                 <dbl>        <int>
##  1 Inversión en Maquinaria/Equipo   399347268.            7
##  2 Otros                            129829168.            7
##  3 Creación/Retención de Empleos     90509631             8
##  4 Inversión en Infraestructura      68483530.            7
##  5 Transferencia de Tecnología        5860000             2
##  6 PYMES Innovadoras                  2490000             5
##  7 Servicios Profesionales            1978967             2
##  8 Industrias Creativas               1968239.            4
##  9 Renta Incentivada                  1483614             1
## 10 Apoyo Empresarial                   325000             1
## 11 Sin Categoría                        50595             1
## 12 Ayuda PYMES Huracán Fiona            10000             1

Plot 4b: Cumulative Cash Grant Amount Per Year by Grant Category (Below $10M Zoom)

## [1] "Categories Below $10M Summary:"
## # A tibble: 8 × 3
##   grant_category_base         total_amount years_active
##   <chr>                              <dbl>        <int>
## 1 Transferencia de Tecnología     5860000             2
## 2 PYMES Innovadoras               2490000             5
## 3 Servicios Profesionales         1978967             2
## 4 Industrias Creativas            1968239.            4
## 5 Renta Incentivada               1483614             1
## 6 Apoyo Empresarial                325000             1
## 7 Sin Categoría                     50595             1
## 8 Ayuda PYMES Huracán Fiona         10000             1

Plot 5: Approved vs Disbursed Funds per Sector (Stacked Bars)

Key Findings & Business Implications

Data Quality Assessment

  • Extraction Challenges: Automated PDF processing revealed significant data harmonization requirements
  • Category Standardization: Multiple variations in grant category naming require systematic consolidation
  • Quality Metrics: Comprehensive data quality framework implemented for future extractions

Strategic Insights

  • Geographic Distribution: Clear patterns in municipal grant allocation across Puerto Rico
  • Company Concentration: Top 5% of companies represent significant portion of total grants
  • Temporal Trends: Year-over-year analysis reveals economic development patterns
  • Category Analysis: Cumulative trends show evolution of incentive program focus

Recommendations

  1. Data Standardization: Implement systematic category harmonization for future reports
  2. Quality Control: Enhanced validation framework for PDF extraction processes
  3. Monitoring Framework: Regular analysis of grant distribution patterns
  4. Strategic Planning: Use insights for economic development policy optimization